Volume 13: Proceedings Applied Energy Symposium: CUE2020, Part 2, Japan/Virtual, 2020

Optimal Power Management Strategy for Parallel HEVs in Acceleration Mode Bo Zhang, Tielong Shen

Abstract

This paper presents a strategy for optimizing the comfortability of hybrid electric powertrains in acceleration mode. A parallel hybrid electrical vehicle (HEV) powertrain system with two motors and single turbo-charged engine is considered, and during the acceleration mode, it is assumed that the desired acceleration rate cannot be satisfied by the electrical motor only. Then, the first challenging issue is how to manage the combustion engine to assist the power generation and the power split such that the system satisfies comfortability, and the second challenging is difficulty in modeling the comfortability, e.g. analytically describing the human feeling. This paper exploits a black- box module to evaluate the comfortability quantitatively which is used in automotive industry. A genetic algorithm (GA) is applied to seek the optimum power split and gear schedule in acceleration mode which improves the comfortability evaluated by the module. Finally, the simulation results conducted on a simulator with practical background are demonstrated where to validate the proposed design approach.

Keywords ride comfort, black-box module, hybrid electric vehicles (HEVs), genetic algorithm (GA)

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