Multi-objective optimization design and performance evaluation for plug-in hybrid electric vehicle powertrains

Xingyu Zhou, Datong Qin and Jianjun Hu

Applied Energy, 2017, vol. 208, issue C, No S0306261917312345, 1608-1625

Abstract: This study provides an optimal selection methodology for plug-in hybrid electric vehicle (PHEV) powertrain configuration by means of optimization and comprehensive evaluation of powertrain design schemes. The challenge of this study is to reveal each powertrain configuration performance potential in different situations of object trade-off and solve the control-physical integrated optimization problem of the PHEV powertrain design. To determine performance potential, a configuration-sizing-control strategy integrated multi-objective powertrain optimization design is proposed and applied to series, parallel pre-transmission (P2), output power-split, and multi-mode power-split powertrain configurations. Firstly, considering simultaneous optimization of fuel economy, electric energy consumption, and acceleration capacity, the parameters of the powertrain components and vehicle performance of each configuration are optimized based on global optimal control in different situations of object trade-off. Then, the Pareto optimal selection of powertrain configuration and its corresponding optimal component parameters are obtained by performance comparison and non-domination sorting. The results suggest that the P2 configuration and its optimal sizing can be selected when the goal is to optimize acceleration capacity, the multi-mode power-split configuration and its optimal sizing can be selected when the goal is to optimize electric energy efficiency, and the output power-split configuration and its optimal sizing can be selected when the fuel economy needs to be optimized.

Keywords: Plug-in hybrid electric vehicle; Powertrain configuration; Multi-objective optimization; Fuel economy; Electric energy consumption; Acceleration capacity (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (2)

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DOI: 10.1016/j.apenergy.2017.08.201

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