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Impact of Engine Dynamics on Optimal Energy Management Strategies for Hybrid Electric Vehicles
Linköping University, Department of Electrical Engineering, Vehicular Systems.
Linköping University, Department of Electrical Engineering, Vehicular Systems.
2018 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

In recent years, rules and regulations regarding fuel consumption of vehicles and the amount of emissions produced by them are becoming stricter. This has led the automotive industry to develop more advanced solutions to propel vehicles to meet the legal requirements. The Hybrid Electric Vehicle is one of the solutions that is becoming more popular in the automotive industry. It consists of an electrical driveline combined with a conventional powertrain, propelled by either a diesel or petrol engine. Two power sources create the possibility to choose when and how to use the power sources to propel the vehicle. The strategy that decides how this is done is referred to as an energy management strategy. Today most energy management strategies only try to reduce fuel consumption using models that describe the steady state behaviour of the engine. In other words, no reduction of emissions is achieved and all transient behaviour is considered negligible. 

In this thesis, an energy management strategy incorporating engine dynamics to reduce fuel consumption and nitrogen oxide emissions have been designed. First, the models that describe how fuel consumption and nitrogen oxide emissions behave during transient engine operation are developed. Then, an energy management strategy is developed consisting of a model predictive controller that combines the equivalent consumption minimization strategy and convex optimization. Results indicate that by considering engine dynamics in the energy management strategy, both fuel consumption and nitrogen oxide emissions can be reduced. Furthermore, it is also shown that the major reduction in fuel consumption and nitrogen oxide emissions is achieved for short prediction horizons.

Place, publisher, year, edition, pages
2018. , p. 79
Keywords [en]
HEV, energy management strategy, EMS, convex optimization, ECOS, model predictive control, MPC, equivalent consumption minimization strategy, ECMS, engine dynamics, NOx
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:liu:diva-148890ISRN: LiTH-ISY-EX--18/5163--SEOAI: oai:DiVA.org:liu-148890DiVA, id: diva2:1222290
External cooperation
Volvo Car Corporation
Subject / course
Vehicular Systems
Supervisors
Examiners
Available from: 2018-06-21 Created: 2018-06-21 Last updated: 2018-06-21Bibliographically approved

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CiteExportLink to record
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