Comparison of architecture and adaptive energy management strategy for plug-in hybrid electric logistics vehicle
Changyin Wei,
Xiuxiu Sun,
Yong Chen,
Libin Zang and
Shujie Bai
Energy, 2021, vol. 230, issue C
Abstract:
This paper deals with the comparison of architecture and adaptive energy management strategy (EMS) for hybrid powertrain system (HPS), including one or two electric motor, an engine and a battery, for a plug-in hybrid electric logistics vehicle (PHELV). The most attractive advantage deriving from HPSs is the possibility of reducing emission and improving fuel economic. For comparison purposes, the series, parallel, and series-parallel hybrid powertrain system are examined by dynamic programming (DP) algorithm using the same vehicular parameters. The approach of adaptive EMS is driving pattern recognition (DPR) to obtain optimum estimation of EMS parameters under different driving cycle. A back propagation (BP) neural network DPR optimized model by an improved genetic algorithm (IGA) has been proposed. Taking the costs of fuel consumption, the parameters of the fuzzy logic controller (FLC) and equivalent consumption minimization strategy (ECMS) are optimized. The comparative results show that the series PHELV fuel economy improvements are 7.60% and 6.53%, compared with parallel and series-parallel PHELV. The difference between the optimal fuzzy energy management strategy and the global optimization is 4.74%, and the ECMS is 4.66%.
Keywords: Energy management strategy; Plug-in hybrid electric logistics vehicle; Fuel economy; Driving pattern recognition (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:230:y:2021:i:c:s0360544221011063
DOI: 10.1016/j.energy.2021.120858
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