Development a new power management strategy for power split hybrid electric vehicles |
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| Institution: | 1. University of Moncton, Moncton, New Brunswick, Canada;2. University of Quebec in Trois-Rivieres, Quebec, Canada;1. Automotive Engineering, Clemson University, Greenville, SC 29607, USA;2. China North Vehicle Research Institute, China;3. Department of Automotive Engineering, Clemson University, Greenville, SC 29607, USA;1. School of Automotive Engineering, Chang''an University, Southern 2nd Road, Xi''an 710064, China;2. State Key Laboratory of Mechanical Transmissions, Department of Automotive Engineering, Chongqing University, Chongqing 400044, China;3. Advanced Vehicle Engineering Centre, Cranfield University, Cranfield, MK43 0AL, UK |
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| Abstract: | Reduction of greenhouse gas emission and fuel consumption as one of the main goals of automotive industry leading to the development hybrid vehicles. The objective of this paper is to investigate the energy management system and control strategies effect on fuel consumption, air pollution and performance of hybrid vehicles in various driving cycles. In order to simulate the hybrid vehicle, the combined feedback–feedforward architecture of the power-split hybrid electric vehicle based on Toyota Prius configuration is modeled, together with necessary dynamic features of subsystem or components in ADVISOR. Multi input fuzzy logic controller developed for energy management controller to improve the fuel economy of a power-split hybrid electric vehicle with contrast to conventional Toyota Prius Hybrid rule-based controller. Then, effects of battery’s initial state of charge, driving cycles and road grade investigated on hybrid vehicle performance to evaluate fuel consumption and pollution emissions. The simulation results represent the effectiveness and applicability of the proposed control strategy. Also, results indicate that proposed controller is reduced fuel consumption in real and modal driving cycles about 21% and 6% respectively. |
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| Keywords: | Power-split hybrid vehicle Energy management Fuzzy logic controller State of charge Pollution emissions and fuel consumption |
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