Economy Optimization by Multi-Strategy Improved Whale Optimization Algorithm Based on User Driving Cycle Construction for Hybrid Electric Vehicles

Nowadays, there is an increasing focus on enhancing the economy of hybrid electric vehicles (HEVs). This study builds a framework model for the parameter optimization of hybrid powertrains in user driving cycles. Unlike the optimization under standard driving cycles, the applied user driving cycle i...

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Vydané v:	Machines (Basel) Ročník 13; číslo 2; s. 158
Hlavní autori:	Ma, Jie, Pan, Mingzhang, Guan, Wei, Zhang, Zhiqing, Zhou, Jingcheng, Ye, Nianye, Qin, Haifeng, Li, Lulu, Man, Xingjia
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Basel MDPI AG 01.02.2025
Predmet:	Accuracy Algorithms Automobiles, Electric Cluster analysis Clustering Driving conditions Economic aspects economic optimization Eigenvalues Electric vehicles Energy consumption Energy efficiency Genetic algorithms HEV Hybrid electric vehicles Hybrid vehicles Literature reviews Marine mammals Markov analysis Mathematical optimization Methods Monte Carlo simulation multi-strategy improved WOA Optimization Parameters Powertrain powertrain parameters user driving cycle construction China
ISSN:	2075-1702, 2075-1702
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Abstract	Nowadays, there is an increasing focus on enhancing the economy of hybrid electric vehicles (HEVs). This study builds a framework model for the parameter optimization of hybrid powertrains in user driving cycles. Unlike the optimization under standard driving cycles, the applied user driving cycle incarnates realistic driving situations, and the optimization results are more realistic. Firstly, the user driving cycle with high accuracy is constructed based on actual driving data, which provides a basis for the performance analysis of HEV. Secondly, the HEV model with good power and economy is constructed under user driving cycles. Finally, a multi-strategy improved whale optimization algorithm (MIWOA) is proposed, which can guarantee better economy of HEV compared with the original whale optimization algorithm (WOA). The economy optimization of HEV is completed by MIWOA under user driving cycles, and the hybrid vehicle economy parameters that are more in line with the user’s actual driving conditions are obtained. After optimization, the 100 km equivalent fuel consumption (EFC) of HEV is reduced by 5.20%, which effectively improves the vehicle’s economy. This study demonstrates the effectiveness of the MIWOA method in improving economy and contributes a fresh thought and method for the economic optimization of the hybrid powertrain.
AbstractList	Nowadays, there is an increasing focus on enhancing the economy of hybrid electric vehicles (HEVs). This study builds a framework model for the parameter optimization of hybrid powertrains in user driving cycles. Unlike the optimization under standard driving cycles, the applied user driving cycle incarnates realistic driving situations, and the optimization results are more realistic. Firstly, the user driving cycle with high accuracy is constructed based on actual driving data, which provides a basis for the performance analysis of HEV. Secondly, the HEV model with good power and economy is constructed under user driving cycles. Finally, a multi-strategy improved whale optimization algorithm (MIWOA) is proposed, which can guarantee better economy of HEV compared with the original whale optimization algorithm (WOA). The economy optimization of HEV is completed by MIWOA under user driving cycles, and the hybrid vehicle economy parameters that are more in line with the user’s actual driving conditions are obtained. After optimization, the 100 km equivalent fuel consumption (EFC) of HEV is reduced by 5.20%, which effectively improves the vehicle’s economy. This study demonstrates the effectiveness of the MIWOA method in improving economy and contributes a fresh thought and method for the economic optimization of the hybrid powertrain.
Audience	Academic
Author	Ye, Nianye Qin, Haifeng Li, Lulu Man, Xingjia Pan, Mingzhang Zhou, Jingcheng Guan, Wei Zhang, Zhiqing Ma, Jie
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SubjectTerms	Accuracy Algorithms Automobiles, Electric Cluster analysis Clustering Driving conditions Economic aspects economic optimization Eigenvalues Electric vehicles Energy consumption Energy efficiency Genetic algorithms HEV Hybrid electric vehicles Hybrid vehicles Literature reviews Marine mammals Markov analysis Mathematical optimization Methods Monte Carlo simulation multi-strategy improved WOA Optimization Parameters Powertrain powertrain parameters user driving cycle construction
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Title	Economy Optimization by Multi-Strategy Improved Whale Optimization Algorithm Based on User Driving Cycle Construction for Hybrid Electric Vehicles
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