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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Bibliographic Details
Published in:Machines (Basel) Vol. 13; no. 2; p. 158
Main Authors: Ma, Jie, Pan, Mingzhang, Guan, Wei, Zhang, Zhiqing, Zhou, Jingcheng, Ye, Nianye, Qin, Haifeng, Li, Lulu, Man, Xingjia
Format: Journal Article
Language:English
Published: Basel MDPI AG 01.02.2025
Subjects:
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
Online Access:Get full text
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Summary: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.
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ISSN:2075-1702
2075-1702
DOI:10.3390/machines13020158