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Development of an online adaptive energy management strategy for the novel hierarchical coupled electric powertrain

This paper develops an online adaptive energy management strategy (EMS) for the promising hierarchical coupled electric powertrain (HCEP) to exert its energy‐saving potential while considering the adaptability to driving conditions and the suppression of mode switching frequency. First, the complex...

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Published in:Energy science & engineering 2021-09, Vol.9 (9), p.1596-1613
Main Authors: Chen, Xianbao, Shu, Hongyu, Song, Yitong
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description This paper develops an online adaptive energy management strategy (EMS) for the promising hierarchical coupled electric powertrain (HCEP) to exert its energy‐saving potential while considering the adaptability to driving conditions and the suppression of mode switching frequency. First, the complex energy management issue of the HCEP is simplified by introducing a simple power allocation method. And, the simplified energy management issue is solved by the Dynamic Programming to obtain the offline optimal working mode sequences of the HCEP. Second, the online working mode decision rules of the HCEP are established according to the obtained working mode sequences. And, the auxiliary rules in the decision rules are further optimized for different types of driving conditions. Then, the principal component analysis and generalized regression neural network are used to construct the driving condition recognizer (DCR) with high prediction accuracy. And, based on the constructed DCR, working mode decision rules, and introduced power allocation method, an online adaptive EMS is developed for the HCEP. Finally, the rationality of the introduced power allocation method and the effectiveness of the developed online adaptive EMS are verified. This paper develops an online adaptive energy management strategy (EMS) for the promising hierarchical coupled electric powertrain (HCEP) applied in vehicles. This online adaptive EMS can not only ensure the energy‐saving effect of the HCEP, but also can effectively avoid frequent working mode switching, as well as has adaptive ability to different driving conditions.
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First, the complex energy management issue of the HCEP is simplified by introducing a simple power allocation method. And, the simplified energy management issue is solved by the Dynamic Programming to obtain the offline optimal working mode sequences of the HCEP. Second, the online working mode decision rules of the HCEP are established according to the obtained working mode sequences. And, the auxiliary rules in the decision rules are further optimized for different types of driving conditions. Then, the principal component analysis and generalized regression neural network are used to construct the driving condition recognizer (DCR) with high prediction accuracy. And, based on the constructed DCR, working mode decision rules, and introduced power allocation method, an online adaptive EMS is developed for the HCEP. Finally, the rationality of the introduced power allocation method and the effectiveness of the developed online adaptive EMS are verified. This paper develops an online adaptive energy management strategy (EMS) for the promising hierarchical coupled electric powertrain (HCEP) applied in vehicles. This online adaptive EMS can not only ensure the energy‐saving effect of the HCEP, but also can effectively avoid frequent working mode switching, as well as has adaptive ability to different driving conditions.</description><identifier>ISSN: 2050-0505</identifier><identifier>EISSN: 2050-0505</identifier><identifier>DOI: 10.1002/ese3.931</identifier><language>eng</language><publisher>London: John Wiley &amp; Sons, Inc</publisher><subject>Adaptability ; Consumption ; Convex analysis ; Driving conditions ; Dynamic programming ; Electric vehicles ; Energy conservation ; Energy efficiency ; Energy management ; energy saving ; hierarchical coupled electric powertrain ; Neural networks ; online adaptive energy management strategy ; Optimization algorithms ; power distribution ; Powertrain ; Principal components analysis ; Traffic ; Wheels ; working mode decision</subject><ispartof>Energy science &amp; engineering, 2021-09, Vol.9 (9), p.1596-1613</ispartof><rights>2021 The Authors. published by the Society of Chemical Industry and John Wiley &amp; Sons Ltd.</rights><rights>2021. 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This paper develops an online adaptive energy management strategy (EMS) for the promising hierarchical coupled electric powertrain (HCEP) applied in vehicles. 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subjects Adaptability
Consumption
Convex analysis
Driving conditions
Dynamic programming
Electric vehicles
Energy conservation
Energy efficiency
Energy management
energy saving
hierarchical coupled electric powertrain
Neural networks
online adaptive energy management strategy
Optimization algorithms
power distribution
Powertrain
Principal components analysis
Traffic
Wheels
working mode decision
title Development of an online adaptive energy management strategy for the novel hierarchical coupled electric powertrain
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