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Languages: English
Types: Doctoral thesis
Subjects: TL

Classified by OpenAIRE into

ACM Ref: ComputerApplications_COMPUTERSINOTHERSYSTEMS
The energy management system (EMS) of hybrid electric vehicle controls the operation of two power plants; electric machine/battery and typically engine. Hence the fuel economy and emissions of hybrid vehicles strongly depend on the EMS. It is known that considering the future trip demand in devising an EMS control strategy enhance the vehicle and component performances. However existing such acausal EMS cannot be used in real time and would require prior knowledge of the trip vehicle speed profile (trip demand). Therefore rule based EMS which considers instantaneous trip demand in devising a control strategy are used. Such causal EMS are real time capable and simple in design. However rule based EMS are tuned for a set of driving cycles and hence their performance is vulnerable in real world driving. The research question is “How to design a real time capable acausal EMS for a plug in hybrid electric vehicle (PHEV) that can adapt to the uncertainties of real world driving”.\ud \ud In the research, the design and evaluation of a proposed EMS to deal and demonstrate in scenarios expected in real world driving respectively were considered. The proposed rule based acausal EMS is formulated over the estimated vehicle trip energy and driving information. Vehicle trip energy is the electric (battery) energy required to meet the trip demand estimated using known driving information. Driving information that can be considered are driver style, route distance and road types like urban and extra urban, with traffic as a sub function. Unlike vehicle speed, vehicle trip energy is shown to be relatively less dynamic in real world driving.\ud \ud For the proposed EMS evaluation, a commonly used parallel PHEV model was simulated. For driving information EMS was not integrated to a navigation system but manually defined. Evaluation studies were done for a driver, and traffic was not considered for simplicity.\ud \ud In the thesis, vehicle performance and credentials for real world applicability (real time capability and adaptability) of the proposed acausal EMS are demonstrated for various scenarios in real world driving; varied initial SOC, sequence of road types, trip distance and trip energy estimation. Over the New European Driving Cycle (NEDC) the proposed EMS vehicle performance is compared to a conventional rule based EMS. The proposed EMS fuel economy improvement is up to 11% with 5 times fewer number of engine stop-starts. Similarly in the validation study, with no prior knowledge of trip vehicle speed profile, the fuel economy improvement is up to 29% with 7 times fewer number of engine stop-starts. The simulation duration of the proposed EMS is as good as conventional rule based EMS. Hence the proposed EMS is potentially real time capable. The proposed EMS can adapt to a wide variation in trip energy (±15%) estimation and still perform better than the conventional rule based EMS. The proposed EMS can tolerate variation in trip demand estimation and no prior knowledge of trip vehicle speed profile is required, unlike other acausal EMS studies in the literature.\ud \ud A new PHEV EMS has been formulated. Through simulation it has been seen to deliver benefit in vehicle performance and real world applicability for varied scenarios as expected in real world driving. The key new step was to use vehicle trip energy in the formulation, which enabled rule based EMS to be acausal and potentially real time capable.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

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    • Vehicle speed, m/s 0 to 5.58
    • 5.58 to 9.05
    • 9.05 to 13.60
    • 13.6 to 18.80
    • Above 18.80
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