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Using Real-World Driving Databases to Generate Driving Cycles with Equivalence Properties
Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
2016 (English)In: IEEE Transactions on Vehicular Technology, ISSN 0018-9545, E-ISSN 1939-9359, Vol. 65, no 6, 4095-4105 p.Article in journal (Refereed) Published
Abstract [en]

Due to the increasing complexity of vehicle design, understanding driver behavior and driving patterns is becoming increasingly more important. Therefore, a large amount of test driving is performed, which together with recordings of normal driving, results in large databases of recorded drives. A fundamental question is how to make best use of these data to devise driving cycles suitable in the development process of vehicles. One way is to generate driving cycles that are representative for the data or for a suitable subset of the data, e.g., regarding geographical location, driving distance, speed range, or many other possible selection variables. Further, to make a fair comparison on two such driving cycles possible, another fundamental requirement is that they should have similar excitation of the vehicle. A key contribution here is an algorithm that combines the two given objectives. A formulation with Markov processes is used to obtain a condensed and effective characterization of the database and to generate candidate driving cycles (CDCs). In addition to that is a method transforming a candidate to an equivalent driving cycle (EqDC) with desired excitation. The method is a general approach but is here based on the components of the mean tractive force (MTF), and this is motivated by a hardware-in-the-loop experiment showing the strong relevance of these MTF components regarding fuel consumption. The result is a new method that combines the generation of driving cycles using real-world driving cycles with the concept of EqDCs.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2016. Vol. 65, no 6, 4095-4105 p.
Keyword [en]
Drive cycle, equivalence measures, equivalent driving cycle (EqDC), mean tractive force (MTF), specific energy, test procedures, vehicle design, vehicle excitation, vehicle propulsion
National Category
Electrical Engineering, Electronic Engineering, Information Engineering Computer Engineering
Identifiers
URN: urn:nbn:se:liu:diva-118101DOI: 10.1109/TVT.2015.2502069ISI: 000380068500022OAI: oai:DiVA.org:liu-118101DiVA: diva2:813179
Note

Funding agencies|Swedish Hybrid Vehicle Centre; Linnaeus Center CADICS

At the time for thesis presentation publication was in status: Manuscript.

Available from: 2015-05-21 Created: 2015-05-21 Last updated: 2016-09-19Bibliographically approved
In thesis
1. Evaluation, Generation, and Transformation of Driving Cycles
Open this publication in new window or tab >>Evaluation, Generation, and Transformation of Driving Cycles
2015 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Driving cycles are important components for evaluation and design of vehicles. They determine the focus of vehicle manufacturers, and indirectly they affect the environmental impact of vehicles since the vehicle control system is usually tuned to one or several driving cycles. Thus, the driving cycle affects the design of the vehicle since cost, fuel consumption, and emissions all depend on the driving cycle used for design. Since the existing standard driving cycles cannot keep up with the changing road infrastructure, the changing vehicle fleet composition, and the growing number of vehicles on the road, which do all cause changes in the driver behavior, the need to get new and representative driving cycles are increasing. A research question is how to generate these new driving cycles so that they are both representative and at the same time have certain equivalence properties, to make fair comparisons of the performance results. Besides generation, another possibility to get more driving cycles is to transform the existing ones into new, different, driving cycles considering equivalence constraints.

With the development of new powertrain concepts the need for evaluation will increase, and an interesting question is how to utilize new developments in dynamometer technology together with new possibilities for connecting equipment. Here a pedal robot is developed to be used in a vehicle mounted in a chassis dynamometer and the setup is used for co-simulation together with a moving base simulator that is connected with a communication line. The results show that the co-simulation can become a realistic driving experience and a viable option for dangerous tests and a complement to tests on a dedicated track or on-road tests, if improvements on the braking and the vehicle feedback to the driver are implemented.

The problem of generating representative driving cycles, with specified excitation at the wheels, is approached with a combined two-step method. AMarkov chain approach is used to generate candidate driving cycles that are then transformed to equivalent driving cycles with respect to the mean tractive force components, which are the used measures. Using an optimization methodology the transformation of driving cycles is formulated as a nonlinear program with constraints and a cost function to minimize. The nonlinear program formulation can handle a wide range of constraints, e.g., the mean tractive force components, different power measures, or available energy for recuperation, and using the vehicle jerk as cost function gives good drivability.

In conclusion, methods for driving cycle design have been proposed where new driving cycles can either be generated from databases, or given driving cycles can be transformed to fulfill certain equivalence constraints, approaching the important problem of similar but not the same. The combination of these approaches yields a stochastic and general method to generate driving cycles with equivalence properties that can be used at several instances during the product development process of vehicles. Thus, a powerful and effective engineering tool has been developed.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2015. 17 p.
Series
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1669
National Category
Electrical Engineering, Electronic Engineering, Information Engineering Computer Engineering
Identifiers
urn:nbn:se:liu:diva-117549 (URN)10.3384/diss.diva-117549 (DOI)978-91-7519-065-5 (print) (ISBN)
Public defence
2015-06-10, Visionen, Hus B, Campus Valla, Linköping, 10:15 (English)
Opponent
Supervisors
Available from: 2015-05-21 Created: 2015-05-04 Last updated: 2015-05-21Bibliographically approved

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