<p>This thesis is an approach to improve a two-mode hybrid electric vehicle, which is currently under development by GM, with respect to fuel consumption. The study is not only restricted to the specific two-mode HEV but also presents results regarding parallel as well as serial HEV’s. GM whishes to verify if the online-based controller in the prototype vehicle utilizes the most of the HEV ability and if there is more potential to lower the fuel consumption. The purpose is that the results and conclusions from this work are to be implemented in the controller to further improve the vehicle’s performance. To analyze the behavior of the two-mode HEV and to see where improvements can be made, models of its driveline and components are developed with a focuson losses and efficiency. The models are implemented in MATLAB together with an optimization algorithm based on Dynamic Programming. The models are validated against data retrieved from the prototype vehicle and various cases with different inputs is set up and optimized over the NEDC cycle. Compensation for cold starts and NOx emissions are also implemented in the final model. Deliberate simplifications are made regarding the modeling of the power split’s functionality due to the limited amount of time available for this thesis. The optimizations show that there is potential to lower the fuel consumptionfor the two-mode HEV. The results are further analyzed and the behavior of the engine, motors/generators and battery are compared with recorded data from a prototype vehicle and summarized to a list of suggestions to improve fuel economy.</p>

This thesis is an approach to improve a two-mode hybrid electric vehicle, which is currently under development by GM, with respect to fuel consumption. The study is not only restricted to the specific two-mode HEV but also presents results regarding parallel as well as serial HEV’s. GM whishes to verify if the online-based controller in the prototype vehicle utilizes the most of the HEV ability and if there is more potential to lower the fuel consumption. The purpose is that the results and conclusions from this work are to be implemented in the controller to further improve the vehicle’s performance. To analyze the behavior of the two-mode HEV and to see where improvements can be made, models of its driveline and components are developed with a focuson losses and efficiency. The models are implemented in MATLAB together with an optimization algorithm based on Dynamic Programming. The models are validated against data retrieved from the prototype vehicle and various cases with different inputs is set up and optimized over the NEDC cycle. Compensation for cold starts and NOx emissions are also implemented in the final model. Deliberate simplifications are made regarding the modeling of the power split’s functionality due to the limited amount of time available for this thesis. The optimizations show that there is potential to lower the fuel consumptionfor the two-mode HEV. The results are further analyzed and the behavior of the engine, motors/generators and battery are compared with recorded data from a prototype vehicle and summarized to a list of suggestions to improve fuel economy.

The requirements on fuel consumption and emissions for passenger cars are getting stricter every year. This has forced the vehicle industry to look for ways to improve the performance of the driveline. With the increasing focus on electrification, a common method is to combine an electrical driveline with a conventional driveline that uses a petrol or diesel engine, thus creating a hybrid electric vehicle. To fully be able to utilise the potential of the driveline in such a vehicle, an efficient energy management strategy is needed. This thesis describes the development of an efficient route-based energy management strategy. Three different optimisation strategies are combined, deterministic dynamic programming, equivalent consumption minimisation strategy and convex optimisation, together with segmentation of the input data. The developed strategy shows a decrease in computational time with up to more than one hundred times compared to a benchmark algorithm. When implemented in Volvo's simulation tool, VSim, substantial fuel savings of up to ten percent is shown compared to a charge-depleting charge-sustain strategy.