Life-extending optimal charging for lithium-ion batteries based on a multi-physics model and model predictive control
Recently, battery fast charging strategies have gained increasing interest as range anxiety and long charging time have been the main obstacles to the wider application of electric vehicles. While simply increasing the current can reduce charging time, it might also tend to accelerate the irreversib...
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Veröffentlicht in: | Applied energy 2024-05, Vol.361, p.122918, Article 122918 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Recently, battery fast charging strategies have gained increasing interest as range anxiety and long charging time have been the main obstacles to the wider application of electric vehicles. While simply increasing the current can reduce charging time, it might also tend to accelerate the irreversible capacity degradation and power fade. To solve the dilemma between charging speed and battery lifetime, in this work, we proposed a life-extending optimal charging method that considers the charging time and the aging-related effects within the battery. A multi-physics battery model coupled with thermal and electrochemical degradation dynamics is developed and integrated into a model predictive control framework to manipulate the optimal charging current considering the constraints of safe requirements and the rate of internal aging side reactions. The design method was extensively validated by in-situ and ex-situ experiments. Results show that by reducing the rates of side reactions and minimizing detrimental morphological changes in the anode material, the proposed charging method can prolong the battery lifetime by at least 48.6%, compared with the commonly used constant current and constant voltage charging method without obviously sacrificing charging speed.
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•An electrochemical-thermal-aging battery model is developed and widely validated.•Battery degradation mechanisms are analyzed at various operating conditions.•Optimal charging profile is designed by considering multiple physical constraints.•The impact of algorithm hyper-parameters is discussed.•Capacity loss is reduced by 48.6% without sacrificing the charging speed. |
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ISSN: | 0306-2619 1872-9118 |
DOI: | 10.1016/j.apenergy.2024.122918 |