This paper presents initial work on a context-dependent driver distraction detection algorithm called AttenD2.0, which extends the original AttenD algorithm with elements from the Minimum Required Attention (MiRA) theory. Central to the original AttenD algorithm is a time buffer which keeps track of how often and for how long the driver looks away from the forward roadway. When the driver looks away the buffer is depleted and when looking back the buffer fills up. If the buffer runs empty the driver is classified as distracted. AttenD2.0 extends this concept by adding multiple buffers, thus integrating situation dependence and visual time-sharing behaviour in a transparent manner. Also, the increment and decrement of the buffers are now controlled by both static requirements (e.g. the presence of an on-ramp increases the need to monitor the sides and the mirrors) as well as dynamic requirements (e.g., reduced speed lowers the need to monitor the speedometer). The algorithm description is generic, but a real-time implementation with concrete values for different parameters is showcased in a driving simulator experiment with 16 bus drivers, where AttenD2.0 was used to ensure that drivers are attentive before taking back control after an automated bus stop docking and depot procedure. The scalability of AttenD2.0 relative to available data sources and the level of vehicle automation is demonstrated. Future work includes expanding the concept to real-world environments by automatically integrating situational information from the vehicles environmental sensing and from digital maps.

Hours of service regulations govern the working hours of commercial motor vehicle drivers, but these regulations may become more flexible as highly automated vehicles have the potential to afford periods of in-cab rest or even sleep while the vehicle is moving. A prerequisite is robust continuous monitoring of when the driver is resting (to account for reduced time on task) or sleeping (to account for the reduced physiological drive to sleep). The overall aims of this paper are to raise a discussion of whether it is possible to obtain successful rest during automated driving, and to present initial work on a hypothetical data driven algorithm aimed to estimate if it is possible to gain driving time after resting under fully automated driving. The presented algorithm consists of four central components, a heart rate-based relaxation detection algorithm, a camera-based sleep detection algorithm, a fatigue modelling component taking time awake, time of day and time on task into account, and a component that estimates gained driving time. Real-time assessment of driver fitness is complicated, especially when it comes to the recuperative value of in-cab sleep and rest, as it depends on sleep quality, time of day, homeostatic sleep pressure and on the activities that are carried out while resting. The monotony that characterizes for long-haul truck driving is clearly interrupted for a while, but the long-term consequences of extended driving times, including user acceptance of the key stakeholders, requires further research.

Abstract

SAAB has for a long time used user controlled pilot models in ARES. ARES is a simulation tool used in the desktop environment for simulations and calculations of the JAS 39 Gripen fighter and other aircraft. ARES stands for ”Aircraft Rigid body Engineering Simulation”. To work with these pilot models has been both time-consuming and inefficient. In this master thesis, new pilot models are developed, where parameters are automatically generated, this will result in that the user doesn’t have to put a lot of work into adjusting the gains for different manoeuvres. This is called gain scheduling.

To make this possible, simple models of the aircraft were created at different points in the envelope. These models were then used to calculate optimal controllers using LQ-control and pole placement techniques. These models and controllers were then implemented in Simulink. Simulink was then used to test the controllers before they were implemented in ARES.

Control in all modes except roll attitude and speed by throttle are based on LQ-control in pitch-, roll- and yaw-angular velocity. And through these angular velocities the other angles are controlled by simple controllers, who is generating a reference in angular velocity. The roll attitude controller is based on direct pole placement based upon desired damping and undamped natural frequency, and the speed controller is based upon a model of throttle positions in trimmed states.

The new pilot models are usable to control:

• Roll rate
• Roll attitude
• Pitch rate
• Pitch attitude
• Angle of attack
• Load factor
• Yaw attitude
• Course angle
• Climb angle
• Mach number
• Climb rate

These controllers can be combined so that the aircraft can perform desired maneuvers.

Utilising optimal control presents an opportunity to increase the fuel efficiency in an off-road transport mission conducted by an articulated hauler. A human machine interface (HMI) instructing the hauler operator to follow the fuel optimal vehicle speed trajectory has been developed and tested in real working conditions. The HMI implementation includes a Dynamic Programming based method to calculate the optimal vehicle speed and gear shift trajectories. Input to the optimisation algorithm is road related data such as distance, road inclination and rolling resistance. The road related data is estimated in a map module utilising an Extended Kalman Filter (EKF), a Rauch-Tung-Striebel smoother and a data fusion algorithm. Two test modes were compared: (1) The hauler operator tried to follow the optimal vehicle speed trajectory as presented in the HMI and (2) the operator was given a constant target speed to follow. The objective of the second test mode is to achieve an approximately equal cycle time as for the optimally controlled transport mission, hence, with similar productivity. A small fuel efficiency improvement was found when the human machine interface was used.

A nonlinear mean value engine model (MVEM) of a two-stroke turbocharged marine diesel engine is developed, parameterized and validated against measurement data. The goal is to have a computationally fast and accurate engine model that captures the main dynamics and can be used in the development of control systems for the newly introduced EGR system. The tuning procedure used is explained, and the result is a six-state MVEM with seven control inputs that capture the main system dynamics.

Development of new functionality and smart systems for different types of vehicles is accelerating with the advent of new emerging technologies such as connected and autonomous vehicles. To ensure that these new systems and functions work as intended, flexible and credible evaluation tools are necessary. One example of this type of tool is a driving simulator, which can be used for testing new and existing vehicle concepts and driver support systems. When a driver in a driving simulator operates it in the same way as they would in actual traffic, you get a realistic evaluation of what you want to investigate. Two advantages of a driving simulator are (1.) that you can repeat the same situation several times over a short period of time, and (2.) you can study driver reactions during dangerous situations that could result in serious injuries if they occurred in the real world. An important component of a driving simulator is the vehicle model, i.e., the model that describes how the vehicle reacts to its surroundings and driver inputs. To increase the simulator realism or the computational performance, it is possible to divide the vehicle model into subsystems that run on different computers that are connected in a network. A subsystem can also be replaced with hardware using so-called hardware-in-the-loop simulation, and can then be connected to the rest of the vehicle model using a specified interface. The technique of dividing a model into smaller subsystems running on separate nodes that communicate through a network is called distributed simulation.

This thesis investigates if and how a distributed simulator design might facilitate the maintenance and new development required for a driving simulator to be able to keep up with the increasing pace of vehicle development. For this purpose, three different distributed simulator solutions have been designed, built, and analyzed with the aim of constructing distributed simulators, including external hardware, where the simulation achieves the same degree of realism as with a traditional driving simulator. One of these simulator solutions has been used to create a parameterized powertrain model that can be configured to represent any of a number of different vehicles. Furthermore, the driver's driving task is combined with the powertrain model to monitor deviations. After the powertrain model was created, subsystems from a simulator solution and the powertrain model have been transferred to a Modelica environment. The goal is to create a framework for requirement testing that guarantees sufficient realism, also for a distributed driving simulation.

The results show that the distributed simulators we have developed work well overall with satisfactory performance. It is important to manage the vehicle model and how it is connected to a distributed system. In the distributed driveline simulator setup, the network delays were so small that they could be ignored, i.e., they did not affect the driving experience. However, if one gradually increases the delays, a driver in the distributed simulator will change his/her behavior. The impact of communication latency on a distributed simulator also depends on the simulator application, where different usages of the simulator, i.e., different simulator studies, will have different demands. We believe that many simulator studies could be performed using a distributed setup. One issue is how modifications to the system affect the vehicle model and the desired behavior. This leads to the need for methodology for managing model requirements. In order to detect model deviations in the simulator environment, a monitoring aid has been implemented to help notify test managers when a model behaves strangely or is driven outside of its validated region. Since the availability of distributed laboratory equipment can be limited, the possibility of using Modelica (which is an equation-based and object-oriented programming language) for simulating subsystems is also examined. Implementation of the model in Modelica has also been extended with requirements management, and in this work a framework is proposed for automatically evaluating the model in a tool.

Modern vehicles are complex systems. Different design stages for such a complex system include evaluation using models and submodels, hardware-in-the-loop systems and complete vehicles. Once a vehicle is delivered to the market evaluation continues by the public. One kind of tool that can be used during many stages of a vehicle lifecycle is driving simulators.

The use of driving simulators with a human driver is commonly focused on driver behavior. In a high fidelity moving base driving simulator it is possible to provide realistic and repetitive driving situations using distinctive features such as: physical modelling of driven vehicle, a moving base, a physical cabin interface and an audio and visual representation of the driving environment. A desired but difficult goal to achieve using a moving base driving simulator is to have behavioral validity. In other words, \A driver in a moving base driving simulator should have the same driving behavior as he or she would have during the same driving task in a real vehicle.".

In this thesis the focus is on high fidelity moving base driving simulators. The main target is to improve the behavior validity or to maintain behavior validity while adding complexity to the simulator. One main assumption in this thesis is that systems closer to the final product provide better accuracy and are perceived better if properly integrated. Thus, the approach in this thesis is to try to ease incorporation of such systems using combinations of the methods hardware-in-the-loop and distributed simulation. Hardware-in-the-loop is a method where hardware is interfaced into a software controlled environment/simulation. Distributed simulation is a method where parts of a simulation at physically different locations are connected together. For some simulator laboratories distributed simulation is the only feasible option since some hardware cannot be moved in an easy way.

Results presented in this thesis show that a complete vehicle or hardware-in-the-loop test laboratory can successfully be connected to a moving base driving simulator. Further, it is demonstrated that using a framework for distributed simulation eases communication and integration due to standardized interfaces. One identified potential problem is complexity in interface wrappers when integrating hardware-in-the-loop in a distributed simulation framework. From this aspect, it is important to consider the model design and the intersections between software and hardware models. Another important issue discussed is the increased delay in overhead time when using a framework for distributed simulation.

Moving base driving simulators, with an enclosed human driver, are often used to study driver-vehicle interaction or driver behaviour. Reliable results from such a driving simulator study strongly depend on the perceived realism by the driver in the performed driving task. Assuring sufficient fidelity for a vehicle dynamics model during a driving task is currently to a large degree a manual task. Focus here is to automate this process by employing a framework using collected driving data for detection of model quality for different driving tasks. Using this framework, a powertrain model credibility is predicted and assessed. Results show that chosen powertrain model is accurate enough for a driving scenario on rural roads/motorway, but need improvements for city driving. This was expected, considering the complexity of the vehicle dynamics model, and it was accurately captured by the proposed framework which includes real-time information to the simulator operator.

The automotive industry is facing a major challenge to reduce environmental impacts. As a consequence, the increasing diversity of powertrain configurations put a demand on testing and evaluation procedures. One of the key tools for this purpose is simulators. In this paper a powertrain model and a procedure for parameterizing it, using chassis dynamometers and a developed pedal robot are presented. The parameterizing procedure uses the on-board diagnostics of the car and does not require any additional invasive sensors.

Thus, the developed powertrain model and parameterization procedure provide a rapid non- invasive way of modelling powertrains of test cars. The parameterizing procedure has been used to model a front wheel drive Golf V with a 1.4L multi-fuel engine and a manual gearbox. The achieved results show a good match between simulation results and test data. The powertrain model has also been tested in real-time in a driving simulator.

This Licentiate of Engineering thesis concerns modelling and simulation of hydraulic percussion units. These units are often found in equipment for breaking or drilling in rock and concrete, and are also often driven by oil hydraulics, in which complex fluid-structure couplings are essential for their operation.

Current methodologies used today when developing hydraulic percussion units are based on decoupled analyses, which are not correctly capturing the important coupled mechanisms. Hence, an efficient method for coupled simulations is of high importance, since these mechanisms are critical for the function of these units. Therefore, a co-simulation approach between a 1D system simulation model representing the fluid system and a structural 3D FE-model is proposed.

This approach is presented in detail, implemented for two well-known simulation tools and evaluated for a simple but relevant model. The Hopsan simulation tool was used for the fluid system and the FE-simulation software LS-DYNA was used for the structural mechanics simulation. The co-simulation interface was implemented using the Functional Mock-up Interface-standard.

The approach was further developed to also incorporate multiple components for coupled simulations. This was considered necessary when models for the real application are to be developed. The use of two components for co-simulation was successfully evaluated for two models, one using the simple rigid body representation, and a second where linear elastic representations of the structural material were implemented.

An experimental validation of the co-simulation approach applied to an existing hydraulic hammer was performed. Experiments on the hydraulic hammer were performed using an in-house test rig, and responses were registered at four different running conditions. The co-simulation model was developed using the same approach as before. The corresponding running conditions were simulated and the responses were successfully validated against the experiments. A parameter study was also performed involving two design parameters with the objective to evaluate the effects of a parameter change.

This thesis consists of two parts, where Part I gives an introduction to the application, the simulation method and the implementation, while Part II consists of three papers from this project.

In this study a previously developed co-simulation method that is based on a 1D system model representing the fluid components of a hydraulic machinery, within which structural 3D Finite Element (FE) models can be incorporated for detailed simulation of specific sub-models or complete structural assemblies, is further developed. The fluid system model consists of ordinary differential equation sub-models that are computationally very inexpensive, but still represents the fluid dynamics very well. The co-simulation method has been shown to work very well for a simple model representing a hydraulic driven machinery. A more complex model was set up in this work, in which two cylinders in the hydraulic circuit were evaluated. Such type of models, including both the main piston and control valves, are necessary as they represent the real application to a further extent than the simple model, of only one cylinder. Two models have been developed and evaluated, from the simple rigid body representation of the structural mechanics model, to the more complex model using linear elastic representation. The 3D FE-model facilitates evaluation of displacements, stresses, and strains on a local level of the model. The results can be utilised for fatigue assessment, wear analysis and for predictions of noise radiation.

This thesis studies motion planning for future autonomous vehicles with main focus on passenger cars. By having automatic steering and braking together with information about the environment, such as other participants in the traffic or obstacles, it would be possible to perform autonomous maneuvers while taking limitations of the vehicle and road–tire interaction into account. Motion planning is performed to find such maneuvers that bring the vehicle from the current state to a desired future state, here by formulating the motion-planning problem as an optimal control problem. There are a number of challenges for such an approach to motion planning; some of them are how to formulate the criterion in the motion planning (objective function in the corresponding optimal control problem), and how to make the solution of motion-planning problems efficient to be useful in online applications. These challenges are addressed in this thesis.

As a criterion for motion-planning problems of passenger vehicles on doublelane roads, it is investigated to use a lane-deviation penalty function to capture the observation that it is dangerous to drive in the opposing lane, but safe to drive in the original lane after the obstacle. The penalty function is augmented with certain additional terms to address also the recovery behavior of the vehicle. The resulting formulation is shown to provide efficient and steady maneuvers and gives a lower time in the opposing lane compared to other objective functions. Under varying parameters of the scenario formulation, the resulting maneuvers are changing in a way that exhibits structured characteristics.

As an approach to improve efficiency of computations for the motion-planning problem, it is investigated to segment motion planning of the full maneuver into several smaller maneuvers. A way to extract segments is considered from a vehicle dynamics point of view, and it is based on extrema of the vehicle orientation and the yaw rate. The segmentation points determined using this approach are observed to allow efficient splitting of the optimal control problem for the full maneuver into subproblems.

Having a method to segment maneuvers, this thesis further studies methods to allow parallel computation of these maneuvers. One investigated method is based on Lagrange relaxation and duality decomposition. Smaller subproblems are formulated, which are governed by solving a low-complexity coordination problem. Lagrangian relaxation is performed on a subset of the dynamic constraints at the segmentation points, while the remaining variables are predicted. The prediction is possible because of the observed structured characteristics resulting from the used lane-deviation penalty function. An alternative approach is based on adoption of the alternating augmented Lagrangian method. Augmentation of the Lagrangian allows to apply relaxation for all dynamic constraints at the segmentation points, and the alternating approach makes it possible to decompose the full problem into subproblems and coordinating their solutions by analytically solving an overall coordination problem. The presented decomposition methods allow computation of maneuvers with high correspondence and lower computational times compared to the results obtained for solving the full maneuver in one step.

Segmenting a motion-planning problem into smaller subproblems could be beneficial in terms of computational complexity. This observation is used as a basis for a new sub-maneuver decomposition approach investigated in this paper in the context of optimal evasive maneuvers for autonomous ground vehicles. The recently published alternating augmented Lagrangianmethod is adopted and leveraged on, which turns out to fit the problem formulation with several attractive properties of the solution procedure. The decomposition is based on moving the coupling constraints between the sub-maneuvers into a separate coordination problem, which is possible to solve analytically. The remaining constraints and the objective function are decomposed into subproblems, one for each segment, which means that parallel computation is possible and benecial. The method is implemented and evaluated in a safety-critical double lane-change scenario. By using the solution of a low-complexity initialization problem and applying warm-start techniques in the optimization, a solution is possible to obtain after just a few alternating iterations using the developed approach. The resulting computational time is lower than solving one optimization problem for the full maneuver.

Autonomous vehicles allow utilisation of new optimal driving approaches that increase vehicle safety by combining optimal all-wheel braking and steering even at the limit of tyre-road friction. One important case is an avoidance manoeuvre that, in previous research, for example, has been approached by different optimisation formulations. An avoidance manoeuvre is typically composed of an evasive phase avoiding an obstacle followed by a recovery phase where the vehicle returns to normal driving. Here, an analysis of the different aspects of the recovery phase is presented, and a subsequent formulation is developed in several steps based on theory and simulation of a double lane-change scenario. Each step leads to an extension of the optimisation criterion. Two key results are a theoretical redundancy analysis of wheel-torque distribution and the subsequent handling of it. The overall contribution is a general treatment of the recovery phase in an optimisation framework, and the method is successfully demonstrated for three different formulations: lane-deviation penalty, minimum time, and squared lateral-error norm.

Avoidance maneuvers at normal driving speed or higher are demanding driving situations that force the vehicle to the limit of tire-road friction in critical situations. To study and develop control for these situations, dynamic optimization has been in growing use in research. One idea to handle such optimization computations effectively is to divide the total maneuver into a sequence of sub-maneuvers and to associate a segmented optimization problem to each sub-maneuver. Here, the alternating augmented Lagrangian method is adopted, which like many other optimization methods benefits strongly from a good initialization, and to that purpose a method with motion candidates is proposed to get an initially feasible motion. The two main contributions are, firstly, the method for computing an initially feasible motion that is found to use obstacle positions and progress of vehicle variables to its advantage, and secondly, the integration with a subsequent step with segmented optimization showing clear improvements in paths and trajectories. Overall, the combined method is able to handle driving scenarios at demanding speeds.

Autonomous vehicles hold promise for increased vehicle and traffic safety, and there are several developments in the field where one example is an avoidance maneuver. There it is dangerous for the vehicle to be in the opposing lane, but it is safe to drive in the original lane again after the obstacle. To capture this basic observation, a lane-deviation penalty (LDP) objective function is devised. Based on this objective function, a formulation is developed utilizing optimal all-wheel braking and steering at the limit of road-tire friction. This method is evaluated for a double lane-change scenario by computing the resulting behavior for several interesting cases, where parameters of the emergency situation such as the initial speed of the vehicle and the size and placement of the obstacle are varied, and it performs well. A comparison with maneuvers obtained by minimum-time and other lateral-penalty objective functions shows that the use of the considered penalty function decreases the time that the vehicle spends in the opposing lane.

Driver fatigue has received increased attention during recent years and is now considered to be a major contributor to approximately 15-30% of all crashes. However, little is known about fatigue in city bus drivers. It is hypothesized that city bus drivers suffer from sleepiness, which is due to a combination of working conditions, lack of health and reduced sleep quantity and quality. The overall aim with the current study is to investigate if severe driver sleepiness, as indicated by subjective reports of having to fight sleep while driving, is a problem for city based bus drivers in Sweden and if so, to identify the determinants related to working conditions, health and sleep which contribute towards this. The results indicate that driver sleepiness is a problem for city bus drivers, with 19% having to fight to stay awake while driving the bus 2-3 times each week or more and nearly half experiencing this at least 2-4 times per month. In conclusion, severe sleepiness, as indicated by having to fight sleep during driving, was common among the city bus drivers. Severe sleepiness correlated with fatigue related safety risks, such as near crashes.

Simulation is often used as a technique to test and evaluate systems, as it provides a cost-efficient and safe alternative for testing and evaluation. A combination of simulators can be used to create high-fidelity and realistic test scenarios, especially when the systems-under-test are complex. An example of such complex systems is Cooperative Intelligent Transport Systems (C-ITS), which include many actors that are connected to each other via wireless communication in order to interact and cooperate. The majority of the actors in the systems are vehicles equipped with wireless communication modules, which can range from fully autonomous vehicles to manually driven vehicles. In order to test and evaluate C-ITS, this paper presents a distributed simulation framework that consists of (a) a moving base driving simulator; (b) a real-time vehicle simulator; and (c) network and traffic simulators. We present our approach for connecting and co-simulating the simulators. We report on limitation and performance that this simulation framework can achieve. Lastly, we discuss potential benefits and feasibility of using the simulation framework for testing of C-ITS.

For several years, there has been a remarkable increase in efforts to develop an autonomous car. Autonomous car systems combine various techniques of recognizing the environment with the help of the sensors and could drastically bring down the number of accidents on road by removing human conduct errors related to driver inattention and poor driving choices.

In this research thesis, an algorithm for jointly ego-vehicle motion and road geometry estimation for Advanced Driver Assistance Systems (ADAS) is developed. The measurements are obtained from the inertial sensors, wheel speed sensors, steering wheel angle sensors, and camera. An Unscented Kalman Filter (UKF) is used for estimating the states of the non-linear system because UKF estimates the state in a simplified way without using complex computations. The proposed algorithm has been tested on a winding and straight road. The robustness and functioning of our algorithm have been demonstrated by conducting experiments involving the addition of noise to the measurements, reducing the process noise covariance matrix, and increasing the measurement noise covariance matrix and through these tests, we gained more trust in the working of our tracker. For evaluation, each estimated parameter has been compared with the reference signal which shows that the estimated signal matches the reference signal very well in both scenarios. We also compared our joint algorithm with individual ego-vehicle and road geometry algorithms. The results clearly show that better estimates are obtained from our algorithm when estimated jointly instead of estimating separately.

In the pursuit of reducing fuel consumption and meeting stringent emission regulations,controlling the air charge in heavy-duty vehicle combustion engines is critical. Instead ofthe traditional way of controlling an engine, which means using separate feed-forward andfeedback, this study explores the usage of a Nonlinear Model Predictive Control (NMPC). Anengine model, describing a physical engine, has been constructed and parameterized withdata from the engine manufacturer. Sub models were parameterized using the least squaremethods. With complete model parametrization, this report shows results of the minimizingof a cost-function that optimizes parameter values according to model-faults.

Two solvers were used and compared for a simplified example, controlling a throttle.Both leading to similar results. One of the solvers were further used to control the completeengine model. The objective was to achieve a desired combustion, minimize losses andthereby reducing emissions. The NMPC was simulated in two different drive cycles.

The results showed that a satisfactory engine model has to be used in the controller toachieve optimal control. Several results show that this method of controlling an engine canbe beneficial. 

Hydraulic hybrid drives are one potential way of improving the fuel efficiency of vehicles, including the possi-bility of recuperating braking energy in a hydraulic accumulator. The high power density of fluid power is mainly advantageous for heavy vehicles, or duty cycles characterized with frequent braking and acceleration. For smaller vehicles, hydraulic hybrid drives are thus most interesting under urban and suburban driving conditions. Amongst the existing architectures, the series hydraulic hybrid offers the advantage of operating the internal combustion engine independently of the vehicle speed, at the cost of a less efficient transmission path than a purely mechanical one. Previously, a series hydraulics hybrid light-duty vehicle was modelled in the transmission-line modelling (TLM)-based simulation software Hopsan from the division of Fluid and Mechatronic Systems (Flumes) at Linköping University. This paper studies through simulation-based optimi-zation how the fuel-optimal vehicle design is affected by various mixes of urban and suburban driving requirements. Both the system’s hardware and the parameters of a basic control strategy are considered. The results show quite similar designs for most performance requirements combinations, and can be the base for further studies addressing additional requirements, conditions and objectives.

Simulation-based optimization is a useful tool in the design of complex engineering products. Simulation models are used to capture numerous aspects of the design problem for the objective function. Optimization results obtained can be assessed from various perspectives. In this study, component and control optimization of a series hydraulic hybrid vehicle is used as an application, and different robustness and performance aspects are evaluated. Owing to relatively high computational loads, efficient optimization algorithms are important to provide sufficient quality of results at reasonable computational costs. To estimate problem complexity and evaluate optimization algorithm performance, the definitions for information entropy and the related performance index are extended. The insights gained from various simulation-based optimization experiments and their subsequent analysis help characterize the efficiency of the optimization problem formulation and parameterization, as well as optimization algorithm selection with respect to parallel computation capabilities for further development of the model and optimization framework.

Driver fatigue is a contributing factor in about 20% of all fatal road crashes worldwide. Countermeasures are urgently needed and one of the most promising and currently available approaches for that are in-vehicle systems for driver fatigue detection. The main objective of this paper is to present a video-based driver sleepiness detection system set up as a two-stage model with (1) a generic deep feature extraction module combined with (2) a personalised sleepiness detection module. The approach was designed and evaluated using data from 13 drivers, collected during naturalistic driving conditions on a motorway in Sweden. Each driver performed one 90-minute driving session during daytime (low sleepiness condition) and one session during night-time (high sleepiness condition). The sleepiness detection model outputs a continuous output representing the Karolinska Sleepiness Scale (KSS) scale from 1-9 or a binary decision as alert (defined as KSS 1-6) or sleepy (defined as KSS 7-9). Continuous output modelling resulted in a mean absolute error (MAE) of 0.54 KSS units. Binary classification of alert or sleepy showed an accuracy of 92% (sensitivity = 91.7%, specificity = 92.3%, F1 score = 90.4%). Without personalisation, the corresponding accuracy was 72%, while a standard fatigue detection PERCLOS-based baseline method reached an accuracy of 68% on the same dataset. The developed real-time sleepiness detection model can be used in the management of sleepiness/fatigue by detecting precursors of severe fatigue, and ultimately reduce sleepiness-related road crashes by alerting drivers before high levels of fatigue are reached.

The brake system is critical for ensuring safe driving and has been the focus of development for many years. Pneumatic braking technology is commonly used in heavy vehicles,but it results in energy wastage and high service costs. Some countries mandate auxiliarybraking systems to assist in stopping the vehicle in addition to service brakes. One suchsystem is the regenerative braking system, which captures kinetic energy from braking andconverts it into electrical energy. Retarders are another commonly used auxiliary brakingsystem. These systems are essential due to heavy vehicle weight, which can weaken servicebrake performance.This thesis focuses on estimating net forces on the truck’s driven axle to understandhow auxiliary braking systems and vehicle traction affect the normal force on the drivenwheel axle. The expected result can assist in maintaining the slip ratio and increasing thelife span and performance of brakes.Scania uses a function to estimate forces on the driven axle and drive wheel slip. Theyneed to determine the normal force on the axle to improve performance of auxiliary brakingsystems, but tests showed that for the same specified slip ratio, the auxiliary braking forcerequired was smaller than that in an acceleration state. Scania believe that dynamic axleload transfer may be the cause, so a 6x2 electrified truck will be investigated in this thesis.The obtained results show the driven wheel axle’s behavior during different dynamicalscenarios.This research aimed to develop a model that can accurately simulate a truck’s movement and estimate the ground reaction force in response to variations in the scenario of thecontrol signal. By studying the quarter car model, bounce-pitch and half car model, theresearchers were able to obtain a model represented by 5 ODEs, which predicts the wheelaxle normal force. To verify the model, data from the CAN bus and measurements using ascale were collected and compared with the model’s output. The Mean Squared Error canbe used to evaluate and compare the model’s performance, and the results showed that themodel provides a reasonable estimate of the normal force on all axles. The study also analyzed the factors that contributed to the errors in the results. The behavior of the normalforce for each wheel axle during acceleration and braking was illustrated, explaining howthe normal force distribution becomes mirrored compared to the acceleration state duringbraking. The study’s discussions enhance the validity of the observed behavior and thereliability of the results.

As the automotive industry constantly makes technological progress, higher demands are placed on safety, environmentally friendly and durability. Modern vehicles are headed towards increasingly complex system, in terms of both hardware and software making it important to detect faults in any of the components. Monitoring the engine’s health has traditionally been done using expert knowledge and model-based techniques, where derived models of the system’s nominal state are used to detect any deviations. However, due to increased complexity of the system this approach faces limitations regarding time and knowledge to describe the engine’s states. An alternative approach is therefore data-driven methods which instead are based on historical data measured from different operating points that are used to draw conclusion about engine’s present state.

In this thesis a proposed diagnostic framework is presented, consisting of a systematically approach for fault classification of known and unknown faults along with a fault size estimation. The basis for this lies in using principal component analysis to find the fault vector for each fault class and decouple one fault at the time, thus creating different subspaces. Importantly, this work investigates the efficiency of taking multiple classifiers into account in the decision making from a performance perspective. Aggregating multiple classifiers is done solving a quadratic optimization problem. To evaluate the performance, a comparison with a random forest classifier has been made.

Evaluation with challenging test data show promising results where the algorithm relates well to the performance of random forest classifier.

The deployment of long combination vehicles (LCVs) is currently in progress in Sweden. LCV refers to heavy vehicles that are longer than 25.25 m, which is the conventional length limit in Swedish regulations. LCVs reduce operational costs, improve fuel efficiency and reduce CO2 emission per ton-km. Despite their numerous advantages, a question that still revolves around these vehicles is how they perform on the road. Although this question has been answered using simulations, an analysis using real traffic data is still missing. 

This thesis assesses the performance of LCVs using naturalistic driving data (NDD). The performance assessment is done using Performance-based standards (PBS) measures. PBS is a regulatory scheme for heavy vehicles, such as LCVs, that includes performance measures with a quantified required level of performance. The main PBS measures used in this thesis are rearward amplification, low-speed swept path, high-speed transient offtracking, and high-speed steady-state offtracking. Rearward amplification represents the amplification of motions in the rear end of a vehicle combination, which relates to its stability, and the remaining three are indicative of the space that the vehicles occupy in different scenarios. The steering reversal rate is also employed to compute the cognitive workload of the drivers in low-speed scenarios. 

Two LCV combinations are considered for analysis, namely an A-double composed of a tractor-semitrailer-dolly-semitrailer/tractor-semitrailer-full trailer and a DuoCAT composed of a truck hauling two centre-axle trailers. Four scenarios are of interest to this thesis: lane changes, manoeuvring through roundabouts, turning in intersections and negotiating tight curves. The thesis presents three contributions outlining the analysis methodologies, followed by a discussion of the results obtained from the analysis. 

The first contribution involves developing an algorithm to extract lane changes from the NDD of LCVs. The algorithm is used against the data obtained from A-doubles. The results indicate that A-doubles adhere to proposed safety limits during lane changes. 

The second contribution assesses the performance of A-double in round-abouts using NDD. Various roundabouts with different radii are considered. The vehicle occupies more space with lower radius roundabouts than higher radius roundabouts. The space occupied in all the cases is below the proposed safety limit. However, steerable axles might be needed for smaller roundabouts than those considered in this study. Additionally, the driver’s cognitive work-load is found to vary with the roundabout’s radius, with drivers navigating higher-radius roundabouts more easily. 

The third contribution deals with the performance evaluation of DuoCAT across four scenarios, followed by the comparison with A-double. The results indicate that the A-double and the DuoCAT are stable and have good tracking performance in most cases. The A-double is observed to be slightly more stable in lane changes, whereas the DuoCAT has slightly better manoeuvrability at low-speed scenarios such as roundabouts and intersections. 

The deployment of High Capacity Transport (HCT) vehicles is in process in different countries. Although their performance has been assessed through simulations and test-track experiments, a question that remains unanswered is: how do these vehicles perform in real traffic? In this paper, the question is addressed for one of the transient manoeuvres, i.e., a lane change using Naturalistic Driving Data (NDD). First, an algorithm is proposed to extract lane changes from the NDD of HCT vehicles using GPS, road data and IMU signals. Following this, the performance of two A-double combinations is assessed in the extracted lane changes using measures commonly used in performance-based standards (PBS) schemes like offtracking and rearward amplification. The dependency of these measures on the factors such as the vehicle’s speed, load and lateral displacement is investigated. The assessment concludes that the vehicles satisfy the PBS requirements proposed for them and are driven safely in the extracted lane changes.

This paper evaluates the performance of two different types of long combination vehicles (A-double and DuoCAT) using naturalistic driving data across four scenarios: lane changes, manoeuvring through roundabouts, turning in intersections, and negotiating tight curves. Four different performance-based standards measures are used to assess the stability and tracking performance of the vehicles: rearward amplification, high-speed transient offtracking, low-speed swept path, and high-speed steady-state offtracking. Also, the steering reversal rate metric is employed to estimate the cognitive workload of the drivers in low-speed scenarios. In the majority of the identified cases of the four scenarios, both combination types have a good performance. The A-double shows slightly better stability in high-speed lane changes, while the DuoCAT has slightly better manoeuvrability at low-speed scenarios like roundabouts and intersections.

A turbocharger’s performance is measured in a gas stand in order to provide information of the components characteristics. The measurement procedure is a very time consuming process and it is thus desired to make it more time-efficient.

To allow for development of an enhanced control strategy used during the measurements, a 0D model of a gas stand is developed. The physical gas stand components are modeled and validated against measurements, all showing a reasonable result. Turbocharger heat transfers are investigated and modeled using a lumped capacitance approach. The heat transfer models shows approximative results when comparing with measurements which is explained by the lack of temperature measurement made on the bearing housing.

When the complete gas stand model is validated against measurements, an improvement of the measurement procedure is examined. By adding an idealized heat source with the possibility to heat the compressor housing, it is possible to reduce the time it takes to reach an equilibrium when switching between two steady state operating points. 

The latest trend within the air force industry is development of unmanned aerial vehicles. The Swedish defense industry group Saab AB is following this trend by means of the introduction of their unmanned helicopter Skeldar V-150. As part of the further development of this system Saab has plans on introducing a marine version of the system, called Skeldar M. One of the purposes of this version is to enable completely autonomous take-offs and landings from ships. To be able to complete this in a safe manner in harsh conditions the helicopter needs to be secured to the deck before take-off as well as after landing.

The purpose of this thesis has been to develop a concept for keeping Skeldar secured on deck. To establish ideas for these concepts a common method for product development has been used. The method involves acquiring customer needs and from these needs establish a list of demands on the product itself. A set of product concepts are then generated by means of creative thinking and competitor analysis. After that the concepts are compared based on how well they meet the demands put upon them and the best ideas get picked out and further developed.

The concepts developed in this thesis stretch from simple ideas where hook and loop fasteners are used to secure the helicopter to more advanced ones where the helicopter’s position relative to the ship is measured and the system adjust to this position. All in all nine basic ideas were developed and a total of twelve versions on securing systems. In consultation with people involved in the Skeldar project, three of the concepts were chosen for further development, one concept where the helicopter was winched to the deck, a second where hook and loop fasteners were used to secure it and finally one where vacuum grippers keeps Skeldar on deck.

With difficulties of implementing a winch system onboard Skeldar as well as on board the ships taken into account, this solution was dropped. This was primarly due to lack of space and difficulties solving an automatic connection between helicopter and ship. The concepts recommended in this thesis will therefore be one of the systems where hook and loop fasteners or vacuum grippers are used.

The need for faster and more reliable logistics solutions is rapidly increasing. This is due to higher demands on the logistical services to improve quality,  quantity, speed and reduce the error tolerance. An arising solution to these increased demands is automated solutions in warehouses, i.e., automated material  handling. In order to provide a satisfactory solution, the vehicles need to be smart and able to solve unexpected situations without human interaction. 

The purpose of this thesis was to investigate if obstacle detection and avoidance in a semi-unknown environment could be achieved based on the data from a 2D LIDAR-scanner. The work was done in cooperation with the development of a new load-handling vehicle at Toyota Material Handling. The vehicle is navigating from a map that is created when the vehicle is introduced to the environment it will be operational within. Therefore, it cannot successfully navigate around new unrepresented obstacles in the map, something that often occurs in a material handling warehouse.

The work in this thesis resulted in the implementation of a modified occupancy grid map algorithm, that can create maps of previously unknown environments if the position and orientation of the AGV are known. The generated occupancy grid map could then be utilized in a lattice planner together with the A* planning algorithm to find the shortest path. The performance was tested in different scenarios at a testing facility at Toyota Material Handling. 

The results showed that the occupancy grid provided an accurate description of the environment and that the lattice planning provided the shortest path, given constraints on movement and allowed closeness to obstacles. However, some performance enhancement can still be introduced to the system which is further discussed at the end of the report. 

The main conclusions of the project are that the proposed solution met the requirements placed upon the application, but could benefit from a more efficient usage of the mapping algorithm combined with more extensive path planning.

The new emission regulations for new trucks was made to decrease the CO2 emissions by 30% from 2020 to 2030. One of the solutions is hybridizing the truck powertrain with 48V or 600V that can recover brake energy with electrical machines and batteries. The control of this hybrid powertrain is key to increase fuel efficiency. The idea behind this approach is to combine two different power sources, an internal combustion engine and a battery driven electric machine, and use both to provide tractive forces to the vehicle. This approach requires a HEV controller to operate the power flow within the systems.

The HEV controller is the key to maximize fuel savings which contains an energy management strategy. It uses the knowledge of the road profile ahead by GPS and maps, and strongly interacts with the control of the cruise speed, automated gear shifts, powertrain modes and state of charge. In this master thesis, the dynamic programming strategy is used as predictive energy management for hybrid electric truck in forward- facing simulation environment. An analysis of predictive energy management is thus done for receding and full horizon length on flat and hilly drive cycle, where fuel consumption and recuperation energy will be regarded as the primary factor. Another important factor to consider is the powertrain mode of the vehicle with different penalty values. The result from horizon study indicates that the long receding horizon length has a benefit to store more recuperative energy. The fuel consumption is decreased for all drive cycle in the comparison with existing Volvo’s strategy.

This paper deals with the control of individual metering systems. This paper deals with the control of an individual metering system that could be used for reducing metering losses by enabling recuperation and regeneration operation. A system that utilizes individual metering is more flexible than a conventional system since there are more control signals and thereby more outputs to control. Energy saving aspects is among the main reasons for the research on this kind of system, but there is also an opportunity of improvements of the dynamics compared to a conventional system. In this paper an approach with LQtechnique are presented for improvements of system dynamics. Since all states in the system can not be measured a state observer is also considered in the control design. These work present simulations, implementations in a real world forwarder application and results from verifying experiments.

In the last decades, there has been a substantial increase in the development of complex active safety systems for automotive vehicles. These systems need to be tested for verification and validation to ensure that the system intervenes in the correct situations using the correct measures. There are multiple methods available to perform such testing. Software-in-the-loop and hardware-in-the-loop testing offer effective driverless testing. Other methods increase the fidelity by including human drivers, such as driving simulators and experiments performed at test tracks.

This thesis examines vehicle-in-the-loop testing, an innovative method where the driver of a real vehicle wears a head-mounted display that displays virtual targets. This method combines the benefits of driving simulators with the benefits of using a real vehicle on a test track. Driving simulators offer repeatability, safety, and the possibility of complex interactions between actors. In contrast, the real vehicle provides the correct vehicle dynamics and motion feedback.

There is a need to know how the technology behind the method might influence the results from vehicle-in-the-loop testing. Two techniques for vehicle-in-the-loop systems are studied. The first involves video-see through head-mounted displays, where the focus of the research is on the effects of visual latency on driving behavior. The results show that lateral driving behavior changes with added latency, but longitudinal behavior appears unaffected. The second system uses an opaque head-mounted display in an entirely virtual world. The research shows that this solution changes speed perception and results in a significant degradation in performance of tasks dependent on visual acuity.

This research presents results that are relevant to consider when developing vehicle-in-the-loop platforms. The results are also applicable when choosing scenarios for this test method.

When engaging a new gear in an automated manual transmission (AMT) the gear needs to be synchronized with the main shaft's angular velocity in the gearbox. This is so that the parts can be connected through a cog wheel and torque can be transferred. To synchronize the angular velocities, mechanical synchronization components can be used. These components synchronize the velocities during the engagement and can be used with larger differences in angular velocities. Should no mechanical synchronization components be used it puts higher demands on the components rotating at similar velocities to avoid mechanical wear and ensure that the gear can be engaged. In today's systems without mechanical synchronization components the gear is engaged when the angular velocities are within a certain difference. This leads to random angle connections between the cogs and gaps that are to be engaged on the gear and main shaft. This can lead to extended or incomplete engages should the components connect cog to cog.

This thesis evaluates the possibility to control the angle at which the components connect by using existing sensor signals in the studied system and known parameters. A model of the system is created and simulated to evaluate the probability of predicting the system over the gear engage. Results indicate that it is possible to predict the connection angle close enough to its real value so that a control strategy could be implemented to control the angle to some level.

An Automated Guided Vehicle (AGV) must follow protective regulations to avoidcrashing into people when autonomously driving in industries. These safety norms require AGVs to enable protective fields, which perform hard braking when objects enter aspecific area in front of the vehicle. Warning fields, or warning systems, are similar fieldsthat decrease the speed of the AGV before objects enter the protective fields to enable asteadier driving. Today at Toyota Material Handling Manufacturing Sweden (TMHMS),warning systems have been implemented but the systems are too sensitive to objects outside of the AGVs path.The purpose of this thesis is to develop a predictive warning system based on empiricaldata from previous driving scenarios. By storing previous positions, the warning systemcould estimate a trajectory based on simple statistics and deploy speed limiting decisionsif objects appear in the upcoming predicted path.The predictive warning system was compared to the current warning system and adeactivated warning system setup in driving performance and driving dynamics. Performance was measured by measuring time to finish an industry-like test track and dynamicswas subjectively rated from a group of experienced AGV developers from TMHMS. Results showed that a predictive warning system drove the test track faster and with betterdynamics than the current warning system and the no warning system setup.Key findings are that a predictive warning system based on empirical data performedbetter in most cases but has some extra requirements to function. Firstly, the method require the AGV to mostly drive on previously driven paths to produce good results. Secondly the warning system requires a somewhat powerful on board computer to handlethe computations. Finally, the warning system requires spatial awareness of pose for thevehicle, as well as structure and shape for deployed protective fields.

Platooning employs a set of technologies to manage how a group of vehicles operates, including radar, GPS and Inter-Vehicular Communication (IVC). It uses broadcasted information such as acceleration, position and velocity to operate vehicle members of the platoon. Cooperation among vehicles allows platoons to reduce fuel consumption and risks associated with driver mistakes. In spite of these benefits, the use of IVC to control vehicles exposes a relevant attack surface that can be exploited by malicious actors. In this paper we study the impact of vulnerabilities associated with the Sybil attack (through falsification of multiple identities) and message falsification in vehicular platooning. Simulation results show that this attack may impact the longitudinal control and compromise the entire platoon control.

With constantly changing regulations on emissions, heavy commercial vehicles manufacturershave to adapt for their products to preserve their quality while meetingthese new requirements. Over the past decades, noise emissions have become a greatconcern and new stricter laws demand companies to decrease their vehicle pass-bynoise target values.To address the requirements from different disciplines, Scania follows a simulationdriven design process to develop new concept models EATS. The collaboration amongengineers from different fields is thereby necessary in order to obtain higher performancesilencers. However, the pre-processing step in terms of acoustic simulationsis time-consuming, which can slow the concept development process.In this thesis, a new method was introduced to automate the pre-processing of silenceracoustic models and allow for design optimisation based on acoustic performanceresults. A common Scania product study case was provided to several theseswithin the NXD organisation. The collaboration among the master thesis workersaimed to demonstrate the benefits of KBE and MDO and how they can be integratedwithin Scania’s current concept development and product introduction processes.The performed work was divided in the following steps: data collection, methoddevelopment and concluding work. The first step consisted in gathering sufficientknowledge by conducting a thorough literature review and interviews. Then, an initialmethod was formulated and tested on a simplified silencer model. Once approvedand verified, the method was applied to the study case EATS.The study case showed that a complex product can have its acoustic pre-processingstep automated by ensuring a good connectivity among the required software anda correct denomination of the geometrical objects involved in the simulations. Themethod investigated how morphological optimisations can be performed at bothglobal and local levels to enhance the transmission loss of a silencer. Besides optimisingthe acoustic performance of the models, the method allowed the identificationof correlations and inter-dependencies among their design variables and ouput parameters.

Automated gear-shifts are critical procedures for the driveline as they are demanded to work as fast and accurate as possible. The torque control of a driveline is especially important for the driver’s feeling of driveability. In the case of gear-shifts and torque control in general, the boost pressure is key to achieve good response and thereby a fast gear-shift.

An experimental study is carried out to investigate the phenomena of boost pressure drop during gear-shift and gather data for the modelling work. Results confirm the stated fact on the influence of boost pressure drop on gear-shift completion time and also indicate a clear linear dependence between initial boost pressure and the following pressure drop.

A dynamic predictive model of the engine is developed with focus on implementation in a heavy duty truck, considering limitations computational complexity and calibration need between truck configurations. The resulting approach is based on a mean value modelling scheme that uses engine control system parameters and functions when possible. To be able to be predictive, a model for demanded torque and engine speed during the gear-shift is developed as reference inputs to the simulation. The simulation is based on a filling and emptying process throughout the engine dynamics, and yields final values of several engine variables such as boost pressure.

The model is validated and later evaluated in comparison to measurements gathered in test vehicle experiments and in terms of robustness to input and model deviations. Computer simulations yield estimations of the boost pressure drop within acceptable limits. Consid- ering estimations used prior to this thesis the performance is good. Input deviations and modelling inaccuracies are found to inflict significant but not devastating deviations to the model output, possibly more over time with ageing of hardware taken into account.

Final implementation in a heavy duty truck ecu is carried out with results indicating that the current implementation of the module is relatively computationally heavy. At the time of ending the thesis it is not possible to analyse its performance further, and it is suggested that the module is optimized in terms of computational efficiency. 

Featured Application This article provides a general overview of technological aspects and limitations of tunnels with respect to smart technologies such as C-ITS. Many smart city applications work with calculated position and time using the Global Navigation Satellite System (GNSS) signals for enhanced precision. However, there are many places where the availability of GNSS is limited, e.g., road tunnels, which are an essential part of transport infrastructure. Tunnels also require greater attention and greater importance of approaches to ensure the safety and security aspects of traffic. The safety, distribution of information, awareness, and smooth traffic can also be ensured by V2X applications, but the current position is also needed. An experimental analysis of data connection and communication availability was performed in the Blanka tunnel (Prague) and its surroundings. The main objective of the work was to find and clearly describe the tunnel blind spots, with an emphasis on communication between cars and potentially between cars and infrastructure. This article summarizes the evaluation results of the V2X tunnel experimental test, the outputs from the analysis of these blind spots, and it provides a future perspective and suggestions that make tunnels smart by using advanced positioning approaches.

Off-road driving operations can be a challenging environment for human conductors as they are subject to accidents, repetitive and tedious tasks, strong vibrations, which may affect their health in the long term. Therefore, they can benefit from a successful implementation of autonomous vehicle technology, improving safety, reducing labor costs and fuel consumption, and increasing operational efficiency. The main contribution of this paper is the experimental validation of a path tracking control strategy, composed of longitudinal and lateral controllers, on an off-road scenario with a fully loaded heavy-duty truck. The longitudinal control strategy relies on a nonlinear model predictive controller, which considers the path geometry and simplified vehicle dynamics to compute a smooth and comfortable input velocity, without violating the imposed constraints. The lateral controller is based on a robust linear quadratic regulator, which considers a vehicle model subject to parametric uncertainties to minimize its lateral displacement and heading error, as well as ensure stability. Experiments were carried out using a fully loaded vehicle on unpaved roads in an open-pit mine. The truck followed the reference path within the imposed constraints, showing robustness and driving smoothness.

Remanufacturing is a value-retaining process that can be adopted to reach a more circular economy. Itpresents a promising opportunity for improving resource efficiency and enhancing sustainable activitiestoday and in the future. This paper contains environmental assessments of remanufactured automotiveparts compared to newly produced parts. The aim is to address the potential of reducing global warmingimpact as well as improving resource and energy efficiency. The result is used to assess the potential ofapplying a remanufacturing strategy to reduce environmental load and to determine the variables that areof major importance. Assumptions, methods, and data are consistently applied for all product groups,making it possible to draw conclusions considering specific characteristics of the different automotiveparts. The results show that collecting used automotive parts (cores) and remanufacturing them leads to asubstantially lower environmental load than when producing new parts. The reuse rate of a core and theenergy used in the remanufacturing process are the main environmental hotspots. Reusing largercomponents primarily affects global warming and energy use, while the type of material is the mainaspect regarding abiotic resources. Energy use is a primary contributing factor considering globalwarming and cumulative energy use. The overall effects due to transports are similar for the two product systems, even though the payload is lower with remanufacturing due to higher share of transports withtrucks.

Volvo Construction Equipment is one of the leading construction machinery manufacturers in the world. To stay amongst the leaders, research and development projects for new technologies are crucial. The most important path of development today is the reduction of emissions produced by these heavy duty vehicles. To tackle this challenge, several technologies are already used in industry. One example are hybrid machines that combine a conventional diesel engine with batteries, resulting in reduced engine size and pollutants. Another option are full battery-electric vehicles, which can reduce the on-site emissions to zero. The electrochemical processes within batteries are however comparable slow and result in long recharge times. A new focus of development within the industry are hybrid systems combining fuel cells and batteries. Since hydrogen can be refueled almost as fast as convenient fuel, it solves the issue of long recharge times. Additionally, the reaction is emission free, since there is no combustion process and the only byproduct that is emitted from the fuel cell is chemically clean water.

This thesis aims to propose an architecture and packaging solution to replace the diesel engine in a large size wheel loader with a fuel cell power system. This also includes all respective auxiliary systems, i.e. energy storage, cooling and electric systems. Achieving the same performance as a conventional large size wheel loader as well as keeping the spatial envelope the same are the main objectives of this work. To achieve these goals, an extensive study on the most common drive cycles is carried out to understand the power demand of the machine. After the selection of an energy storage system based on a MATLAB simulation script, a cooling system is modelled and scaled to fulfill the operating requirements of the different components. Eventually, all systems are modeled and installed into the wheel loader in CATIA V5.

The study showed, that the new system architecture of the vehicle can be fitted into the existing engine bay with a slight extension of the rear frame and hood. Two power optimized batteries are combined with one fuel cell. Hydrogen tanks with a filling volume of 478 [L] can be installed in the machine, covering 50% of the customer population curve without degradation of performance. This includes one refill of the wheel loader during the day. The performance parameters match the conventional machine up to a high degree, concluding that the conversion of a large size wheel loader into a fuel cell powered wheel loader is feasible.

Automotive remanufacturing companies are nowadays facing a wide range ofchallenges. Typical challenges from the point of view of suppliers, producers and customers.Several process steps are analysed and problem fields are dissected: From the core management,to disassembly and cleaning to machining and testing. The main fields of challengesanalysed in this paper are: the vagueness in respect of fiscal value, environmental regulationsand taxation of core parts, the important need for a continuing qualification of staff andengineers, an efficient core management, the adaption of pricing models and the competence tohandle the growing variety and complexity. The focus of this analysis lies on activities of theindependent after-market (IAM) for remanufactured products.

The automotive market is changing. For many years, cars with internal-combustion engines were dominant. Recently, more cars with alternative drive trains have become available, and their market share has increased, a trend that has had an effect on the remanufacturing industry for automotive parts. This paper aims to describe and evaluate the challenges and opportunities in the coming years for the remanufacturing industry as a result of the increasing number and share of electric vehicles. Both theory and empirical data have been used to meet this aim. From theory, the two different drive train concepts of the internal combustion engine and the battery electric vehicle are described, along with the major differences from a remanufacturing standpoint. These differences and effects are described, evaluated, and fully or partly confirmed by industry experts. The results show that future market actors are unset today, less space-consuming machinery parks will be needed, major investments into knowledge and equipment (especially for testing) will be required, and the necessity to handle different kinds of end-of-use/life solutions, especially the recovery for the electric vehicle battery packs, will be a challenge. As future development is still uncertain, the authors recommend that market actors investigate the challenges and opportunities highlighted in this paper and watch future developments carefully.

A key process in a closed-loop supply chain is managing and challenging the transportation and packaging management. Strict environmental regulations in connection with transport of environmentally hazardous substances (e.g. oil) are offering a highcost-saving potential in connection with an optimised transportation and packaging concept. The aim of this case orientated paperis to provide the framework for the management of reverse flow of materials in automotive industry. The emphasis is placed onthe remanufacturing activities. To obtain and verify the necessary information for the above mentioned problems, differentmethods and techniques have been applied: 1) Relevant, available literature in connection with this matter was studied; 2) Dataand documents was requested directly by relevant market actors; 3) The clustered data was analysed and samples werehighlighted; and 4) The data was evaluated and recommended courses of action were given. The results show that the mainproblems appear in the area of forward and reverse logistics: Packaging concepts which do not protect the product in an optimalway (forward / reverse logistics). Moreover, packaging concepts which do not protect the environment against potential negativeinfluence of a used part (reverse logistics) A best practice for the transportation of engine components is given and evaluated: Anengine in a metal frame with oil-pan. Securely attached by bolts. Packed in plastic bag.

A whole head finite element model for simulation of bone conducted (BC) sound transmission was developed. The geometry and structures were identified from cryosectional images of a female human head and eight different components were included in the model: cerebrospinal fluid, brain, three layers of bone, soft tissue, eye, and cartilage. The skull bone was modeled as a sandwich structure with an inner and outer layer of cortical bone and soft spongy bone (diploe) in between. The behavior of the finite element model was validated against experimental data of mechanical point impedance, vibration of the cochlear promontories, and transcranial BC sound transmission. The experimental data were obtained in both cadaver heads and live humans. The simulations showed multiple low-frequency resonances where the first was caused by rotation of the head and the second was close in frequency to average resonances obtained in cadaver heads. At higher frequencies, the simulation results of the impedance were within one standard deviation of the average experimental data. The acceleration response at the cochlear promontory was overall lower for the simulations compared with experiments but the overall tendencies were similar. Even if the current model cannot predict results in a specific individual, it can be used for understanding the characteristic of BC sound transmission in general. (C) 2016 Acoustical Society of America.

Actuation systems for automotive boost control incorporate a vacuum tank and PWM controlled vacuum valves to increase the boosting system flexibility. Physical models for the actuator system are constructed using measurement data from a dynamometer with an engine having a two stage turbo system. The actuator model is integrated in a complete Mean Value Engine Model and a boost pressure controller is constructed. The developed model is used as basis for a nonlinear compensator, that is capable of rejecting disturbances from system voltage. An IMC based boost pressure controller is developed for the vacuum actuator and engine by using the engine model and then tested on the test cell. The controller performance is quantified and system voltage disturbance rejection is demonstrated.

One of the major concerns in the forest industry is the impact on the soil caused by the forest machines duringharvesting, where damages can have a negative impact on e.g. further growth. One of the main reasons is wheel slip.Another concern is the working environment of the operator due to the harsh ground in the forest. Both these issueshave a negative impact on productivity. An attempt to overcome these challenges is made within a collaborative researchproject, which among others also includes Linköping University, where a new six-wheel pendulum arm forwarder isbeing developed. The new forwarder aims at reducing the soil damage by an even pressure distribution and smooth torquecontrol, as well as increased damping of the complete chassis, and thereby improving the working environment. This ispossible since each wheel, driven by its own hydraulic motor, is attached to a pendulum arm allowing to control the heightof each wheel independently of each other. The forwarder has a total maximum weight of 31 tonnes, including 14 tonnesmaximum load. It consists of two steerable joints and is driven by a 360 bhp diesel engine. The transmission consists oftwo hydraulic pumps and six hydraulic motors.This paper deals with the development of the driveline and presents the first experimental tests of the implementedcontrol strategies, where a secondary control approach is chosen for its ability to individually control the torque on eachwheel. The control strategies, presented in the paper, include pressure control, velocity control of the vehicle and ananti-slip controller. To support the development of the control strategies, models of the vehicle and hydraulic subsystemsare derived. The aim with this paper is to verify the concepts on the actual vehicle. The initial results are promising,indicating that the suggested concept is feasible.