Fractional order battery modelling methodologies for electric vehicle applications: Recent advances and perspectives
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actional order battery modelling methodologies for electric vehicle applications: Recent advances and perspectives 1,2
1*
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TIAN JinPeng , XIONG Rui , SHEN WeiXiang & SUN FengChun 1
1
Department of Vehicle Engineering, School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China; 2
Faculty of Science, Engineering and Technology, Swinburne University of Technology, Hawthorn, Victoria 3122, Australia Received April 11, 2020; accepted May 25, 2020; published online August 6, 2020
Accurate modelling of lithium ion batteries is crucial for battery management in electric vehicles. Recent studies have revealed the fractional order nature of lithium ion batteries, leading to fractional order modelling techniques. In this paper, a comprehensive review of the fractional order battery models and their applications in battery management of electric vehicles is provided from the perspectives of frequency and time domains. In the frequency domain, the fractional order models to fit electrochemical impedance spectroscopy data are investigated, followed by their applications in health diagnosis, battery heating and charging strategies. In the time domain, the fractional order models adopted for voltage simulation are discussed, followed by their applications in battery state estimation and fault diagnosis. Finally, from the perspectives of time domain and frequency domain applications, critical challenges and research trends for future work in terms of fractional order modelling are highlighted to advance the development of next-generation battery management. lithium ion battery, fractional calculus, fractional order model, battery management, electric vehicle, electrochemical impedance spectroscopy Citation:
Tian J P, Xiong R, Shen W X, et al. Fractional order battery modelling methodologies for electric vehicle applications: Recent advances and perspectives. Sci China Tech Sci, 2020, 63, https://doi.org/10.1007/s11431-020-1654-0
1 Introduction Lithium ion batteries are dominant energy storage systems in electric vehicles (EVs) owing to their high energy and power density [1,2]. Their performance is determined by both internal states and working conditions, which pose significant challenges in battery management. From the viewpoint of practical applications, a widely accepted battery management methodology is to develop battery models to simulate battery behaviours with known structure and parameters [3]. According to the modelling approach, existing models are categorised into electrochemical models, black-box models and equivalent circuit models (ECMs).
* Corresponding author (email: [email protected])
Electrochemical models mathematically describe electrochemical reactions to simulate battery behaviours. In 1993, Newman et al. [4,5] developed a pseudo-two-dimensional (P2D) model, which includes a number of partial differential equations (PDEs). The P2D model and its variants [6,7] were utilised for different applications, such as state estimation [8], ageing mechanism identification [9] and
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