Article
Engineering, Mechanical
Xinghao Du, Jinhao Meng, Kailong Liu, Yingmin Zhang, Shunli Wang, Jichang Peng, Tianqi Liu
Summary: This paper proposes a co-estimation framework utilizing the advantages of both recursive least squares (RLS) and recursive total least squares (RTLS) for a higher parameter identification performance of the battery equivalent circuit model (ECM). RLS quickly converges by updating the parameters along the gradient of the cost function, while RTLS is applied to attenuate the noise effect once the parameters have converged. Both simulation and experimental results show that the proposed method has good accuracy, a fast convergence rate, and robustness against noise corruption.
CHINESE JOURNAL OF MECHANICAL ENGINEERING
(2023)
Article
Automation & Control Systems
Ruohan Guo, Weixiang Shen
Summary: This article proposes an IA-MAFF-RLS method to identify model parameters of lithium-ion batteries in electric vehicles. The method utilizes information analysis and adaptive strategies to accurately identify the parameters and avoid accuracy loss in model transformation.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2023)
Article
Engineering, Electrical & Electronic
Mouncef El Marghichi, Azeddine Loulijat, Issam El Hantati
Summary: This article proposes a battery parameter update method based on the variable recursive least squares algorithm to improve the accuracy of battery state-of-charge estimation. Comparisons with other methods reveal that the VRLS algorithm outperforms others in terms of predictive performance indicators.
ELECTRICAL ENGINEERING
(2023)
Article
Energy & Fuels
Na Shi, Zewang Chen, Mu Niu, Zhijia He, Youren Wang, Jiang Cui
Summary: This paper proposes an SOC estimation method for lithium-ion batteries based on adaptive extended Kalman filter. By improving parameter identification and adaptively adjusting the forgetting factor, the accurate estimation of SOC is achieved.
JOURNAL OF ENERGY STORAGE
(2022)
Article
Energy & Fuels
Jierui Wang, Wentao Yu, Guoyang Cheng, Lin Chen
Summary: In this paper, a method is proposed to identify the parameters of a fractional-order model (FOM) for Lithium-ion batteries (LIBs) using a synergy of Beetle Antennae Search and Recursive Least Squares. The experimental results show that this method offers a similar modeling accuracy as the Particle Swarm Optimization (PSO), and the online estimated model is more accurate than offline estimated models.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Chemistry, Analytical
You Fu, Binhao Zhai, Zhuoqun Shi, Jun Liang, Zhouhua Peng
Summary: This study proposes an adaptive iterative extended Kalman filter (AIEKF) method for accurate State of Charge (SOC) estimation of lithium-ion batteries in autonomous underwater vehicles (AUVs), addressing the issues of low accuracy and large errors in traditional filtering methods. The experiment results show that the proposed method has high accuracy and fast estimation speed, indicating its great potential for application in AUVs.
Article
Energy & Fuels
Jiaqiang Tian, Siqi Li, Xinghua Liu, Peng Wang
Summary: This paper presents a method for life prediction of lithium-ion batteries based on LSTM neural network. The SOH prediction model is established through dynamic aging experiment and parameter identification improvement, and the effectiveness of the proposed method is verified through experiments.
Review
Chemistry, Physical
Shurong Lei, Song Xin, Shangxiao Liu
Summary: This paper comprehensively reviews the recent development of separate thermal management solutions for electric vehicles (EVs) and discusses in-depth the state-of-the-art integrated solutions. The benefits and drawbacks of each solution are critically commented, and the challenges faced by EV thermal management solutions and their development trends are presented.
JOURNAL OF POWER SOURCES
(2022)
Article
Chemistry, Physical
Yue Pan, Dongsheng Ren, Ke Kuang, Xuning Feng, Xuebing Han, Languang Lu, Minggao Ouyang
Summary: Lithium plating is a severe problem in lithium-ion batteries under low temperature and high charge rates, which can cause capacity fading and safety issues. This paper proposes two detection methods for lithium plating suitable for offline and online use, and verifies their effectiveness through experiments.
JOURNAL OF POWER SOURCES
(2022)
Article
Energy & Fuels
Xiong Shu, Wenxian Yang, Kexiang Wei, Bo Qin, Ronghua Du, Bowen Yang, Akhil Garg
Summary: This study experimentally investigates the degradation of electric vehicle lithium-ion batteries (LIBs) at different temperatures and discharge rates, and proposes a new degradation model to more accurately predict the capacity degradation of EV LIBs. The research reveals that the available capacity of LIBs transiently increases with the increase of charge-discharge cycles during the initial stage of battery use. Temperature has a significant impact on the available capacity of LIBs, and alternating changes in ambient temperature can accelerate the degradation of LIBs. The proposed degradation model exhibits higher prediction accuracy compared to the traditional model.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Engineering, Multidisciplinary
Xin Lai, Jiahui Weng, Yunfeng Huang, Ming Yuan, Yi Yao, Xuebing Han, Yuejiu Zheng
Summary: This study proposes a joint estimation method of state of health (SOH) and state of energy (SOE) using forgetting factor recursive least squares (FFRLS) and unscented Kalman filter algorithm. The method improves the accuracy of SOE estimation under complex and dynamic working conditions.
Article
Electrochemistry
Seyed Saeed Madani, Raziye Soghrati, Carlos Ziebert
Summary: This article proposes an approach to estimate battery capacity based on evaluating the battery's internal resistance and using different least square algorithms. The results show that the method is highly accurate and reliable and can be applied in battery management systems.
Article
Energy & Fuels
Xin Lai, Yunfeng Huang, Xuebing Han, Huanghui Gu, Yuejiu Zheng
Summary: A novel SOE estimation method using PF and EKF algorithms is proposed in this study, which is able to improve accuracy and robustness by identifying battery model parameters at different temperatures. Experimental results show that the maximum error of the proposed algorithm is less than 3% under dynamic conditions and can quickly converge to its reference trajectory even with large initial errors in SOE and total available energy.
JOURNAL OF ENERGY STORAGE
(2021)
Review
Engineering, Environmental
Yang Hua, Xinhua Liu, Sida Zhou, Yi Huang, Heping Ling, Shichun Yang
Summary: Lithium-ion batteries (LIBs) have been widely integrated in renewable resources and electric vehicles due to their advantages. Reuse of EV LIBs holds great potential but faces challenges such as economic, technical, and regulatory issues. Improvements in standardization, big data, and cloud-based technologies are needed for the industrialization of reuse and recycling.
RESOURCES CONSERVATION AND RECYCLING
(2021)
Article
Energy & Fuels
Fan Yang, Dongliang Shi, Kwok-ho Lam
Summary: With the popularization of electric vehicles, accurate estimation of voltage and state-of-charge (SOC) for rechargeable batteries becomes crucial. Traditional extended Kalman Filtering algorithms suffer from limitations in SOC and voltage estimations. This study proposes a modified extended Kalman filtering (MEKF) algorithm to improve the estimation accuracy of voltage and SOC through real-time parameter adjustment and error reduction.
JOURNAL OF ENERGY STORAGE
(2022)
