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Model Predictive Control for Series-Parallel Plug-In Hybrid Electrical Vehicle
Linköping University, Department of Electrical Engineering, Vehicular Systems.
2011 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

The automotive industry is required to deal with increasingly stringent legislationfor greenhouse gases. Hybrid Electric Vehicles, HEV, are gaining acceptance as thefuture path of lower emissions and fuel consumption. The increased complexityof multiple prime movers demand more advanced control systems, where futuredriving conditions also becomes interesting. For a plug-in Hybrid Electric Vehicle,PIHEV, it is important to utilize the comparatively inexpensive electric energybefore the driving cycle is complete, this for minimize the cost of the driving cycle,since the battery in a PIHEV can be charged from the grid. A strategy with lengthinformation of the driving cycle from a global positioning system, GPS, couldreduce the cost of driving. This by starting to blend the electric energy with fuelearlier, a strategy called blended driving accomplish this by distribute the electricenergy, that is charged externally, with fuel over the driving cycle, and also ensurethat the battery’s minimum level reaches before the driving cycle is finished. Astrategy called Charge Depleting Charge Sustaining, CDCS, does not need lengthinformation. This strategy first depletes the battery to a minimum State of Charge,SOC, and after this engages the engine to maintain the SOC at this level. In thisthesis, a variable SOC reference is developed, which is dependent on knowledgeabout the cycle’s length and the current length the vehicle has driven in the cycle.With assistance of a variable SOC reference, is a blended strategy realized. Thisis used to minimize the cost of a driving cycle. A comparison between the blendedstrategy and the CDCS strategy was done, where the CDCS strategy uses a fixedSOC reference. During simulation is the usage of fuel minimized; and the blendedstrategy decreases the cost of the driving missions compared to the CDCS strategy.To solve the energy management problem is a model predictive control used. Thedesigned control system follows the driving cycles, is charge sustaining and solvesthe energy management problem during simulation. The system also handlesmoderate model errors.

Abstract [sv]

Fordonsindustrin måste hantera allt strängare lagkrav mot utsläpp av emissioneroch växthusgaser. Hybridfordon har börjat betraktas som den framtida vägenför att ytterligare minska utsläpp och användning av fossila bränslen. Den ökadekomplexiteten från flera olika motorer kräver mera avancerade styrsystem. Begränsningarfrån motorernas energikällor gör att framtida förhållanden är viktigaatt estimera. För plug-in hybridfordon, PIHEV, är det viktigt att använda denvvijämförelsevis billiga elektriska energin innan fordonet har nått fram till slutdestinationen.Batteriets nuvarande energimängd mäts i dess State of Charge, SOC.Genom att utnyttja information om hur långt det är till slutdestinationen från ettGlobal Positioning System, GPS, blandar styrsystemet den elektriska energin medbränsle från början, detta kallas för blandad körning. En strategi som inte hartillgång till hur långt fordonet ska köras kallas Charge Depleting Charge Sustaining,CDCS. Denna strategi använder först energin från batteriet, för att sedanbörja använda förbränningsmotorn när SOC:s miniminivå har nåtts. Strategin attanvända GPS informationen är jämförd med en strategi som inte har tillgång tillinformation om körcykelns längd. Blandad körning använder en variabel SOC referens,till skillnad från CDCS strategin som använder sig av en konstant referenspå SOC:s miniminivå. Den variabla SOC referensen beror på hur långt fordonethar kört av den totala körsträckan, med hjälp av denna realiseras en blandad körning.Från simuleringarna visade det sig att blandad körning gav minskad kostnadför de simulerade körcyklerna jämfört med en CDCS strategi. En modellbaseradprediktionsreglering används för att lösa energifördelningsproblemet. Styrsystemetföljer körcykler och löser energifördelningsproblemet för de olika drivkällorna undersimuleringarna. Styrsystemet hanterar även måttliga modellfel.

Place, publisher, year, edition, pages
2011. , 55 p.
Keyword [en]
MPC, Model Predictive Control, Plug-In HEV, Quadratic Programming, Hildreths Procedure, Series-Parallel HEV, Split HEV
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-69608ISRN: LiTH-ISY-EX--11/4444--SEOAI: oai:DiVA.org:liu-69608DiVA: diva2:429802
Subject / course
Vehicular Systems
Presentation
2011-05-25, Algoritmen, Linköpings Universitet, Linköping, 16:00 (Swedish)
Uppsok
Technology
Supervisors
Examiners
Available from: 2011-07-06 Created: 2011-07-05 Last updated: 2011-07-06Bibliographically approved

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CiteExportLink to record
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Citation style
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