Review
Green & Sustainable Science & Technology
Jiahui Zhao, Yong Zhu, Bin Zhang, Mingyi Liu, Jianxing Wang, Chenghao Liu, Xiaowei Hao
Summary: The accurate estimation of the state of charge (SOC), the state of health (SOH) and the prediction of remaining useful life (RUL) of lithium-ion batteries is essential for battery management. Researchers have conducted extensive research on battery state evaluation and RUL prediction methods, proposing various approaches. This paper introduces the definitions and existing estimation methods for SOC and SOH, presents the definition of RUL and compares different approaches. Lastly, it summarizes the challenges in lithium-ion battery state estimation and RUL prediction and proposes future directions for development.
Article
Thermodynamics
E. Jiaqiang, Bin Zhang, Yan Zeng, Ming Wen, Kexiang Wei, Zhonghua Huang, Jingwei Chen, Hao Zhu, Yuanwang Deng
Summary: This paper investigates the essence of inconsistency in lithium-ion batteries as State-Of-Charge (SOC) inconsistency, proposing a method to describe battery inconsistency using SOC disparity and studying the equalization control strategy. Through simulations and experiments, it is shown that active equalization significantly improves cell inconsistency and enhances energy utilization in the battery pack during charging and discharging processes. The proposed SOC estimation method meets accuracy requirements, and the equalization strategies effectively minimize SOC and voltage disparities among battery cells.
Article
Electrochemistry
Zhigang Hel, Yingjie Jin, Shuai Hu, Weiquan Li, Xianggang Zhang
Summary: This paper proposes a low computational multi-cell SOC estimation method for lithium batteries in electric vehicles. The method establishes a battery pack difference model based on the equivalent circuit model and uses recursive least squares with forgetting factors to identify model parameters online. A dual adaptive extended Kalman filter algorithm is then constructed to estimate the SOC of all cells in the battery pack. Verification results show that the proposed method significantly reduces estimation time while ensuring accuracy and robustness.
INTERNATIONAL JOURNAL OF ELECTROCHEMICAL SCIENCE
(2022)
Article
Electrochemistry
Zhigang He, Yingjie Jin, Shuai Hu, Weiquan Li, Xianggang Zhang
Summary: This paper proposes a low computational multi-cell SOC estimation method, using recursive least squares and dual adaptive extended Kalman filter algorithm to achieve the SOC estimation of all cells in a series battery pack, verification results show that the method can significantly reduce estimation time.
INTERNATIONAL JOURNAL OF ELECTROCHEMICAL SCIENCE
(2022)
Article
Chemistry, Physical
Haonan Dong, Wei Huang, Yixin Zhao
Summary: This paper presents a method for SOC estimation in battery packs, which includes a mean-model and difference-models, and proposes a low-complexity algorithm for SOC estimation. The established model can accurately track the changing of SOC with reduced computational cost.
JOURNAL OF POWER SOURCES
(2021)
Article
Thermodynamics
Xin Lai, Yunfeng Huang, Huanghui Gu, Xuebing Han, Xuning Feng, Haifeng Dai, Yuejiu Zheng, Minggao Ouyang
Summary: The study proposes an RDE estimation method based on future load prediction, using HMM to predict battery future load, conducting capacity tests at different temperatures, and updating battery model parameters online using the FFRLS algorithm to improve accuracy and robustness.
Article
Multidisciplinary Sciences
Pei Tang, Jusen Hua, Pengchen Wang, Zhonghui Qu, Minnan Jiang
Summary: The article introduces a method to improve the prediction accuracy of the charging state of lithium-ion batteries. By extracting data feature information from different dimensions, the model achieves accurate predictions, as demonstrated by the test results.
SCIENTIFIC REPORTS
(2023)
Article
Electrochemistry
Nataliya N. Yazvinskaya, Mikhail S. Lipkin, Nikolay E. Galushkin, Dmitriy N. Galushkin
Summary: This paper shows that the Peukert generalized equations can be used for capacity estimation of automotive-grade lithium-ion batteries and the parameters in these equations have clear physical meanings. It is also demonstrated that the dependence of the released capacity of lithium-ion batteries on the discharge current reflects the phase transition statistical pattern in the electrodes' active substance.
Article
Energy & Fuels
Shuzhi Zhang, Nian Peng, Haibin Lu, Rui Li, Xiongwen Zhang
Summary: This paper presents a systematic and low-complexity multi-state estimation framework for a series-connected lithium-ion battery pack under passive balance control. The framework includes the estimation of pack state-of-charge (SOC), state-of-health (SOH), and cell SOC inconsistencies. The results show that the proposed framework can accurately estimate the battery pack's states and track the cell SOC inconsistencies.
JOURNAL OF ENERGY STORAGE
(2022)
Article
Energy & Fuels
Shulin Liu, Xia Dong, Xiaodong Yu, Xiaoqing Ren, Jinfeng Zhang, Rui Zhu
Summary: This paper presents an adaptive unscented Kalman filter algorithm (AUKF) for the joint estimation of SOC and SOH of lithium-ion batteries. The proposed method is verified to be accurate and reliable through experiments.
Article
Thermodynamics
Xitian He, Bingxiang Sun, Weige Zhang, Xiaojia Su, Shichang Ma, Hao Li, Haijun Ruan
Summary: This paper proposes a novel battery pack inconsistency method based on variational auto-encoder (VAE), which can preserve the correlation between parameters by training the neural network with small samples. Simulation results show that compared with Copula-based and Metropolis-Hastings-based methods, the VAE-based method can maintain similarity with the original parameters in both parameters distribution and parameters correlation.
Article
Electrochemistry
Xin Lai, Jiahui Weng, Yipeng Yang, Changqing Qiu, Yunfeng Huang, Ming Yuan, Yi Yao, Yuejiu Zheng
Summary: In this study, a method for estimating the remaining discharge energy (RDE) of lithium-ion batteries based on average working condition prediction and multi-parameter updating is proposed. Online identification of battery's ohmic resistance, introduction of temperature-aging factor, and estimation of OCV-SOC by curve scaling are performed. Future working conditions are predicted based on average working condition prediction with less calculation, and the RDE is then estimated under complex working conditions. Experimental results show that the RDE estimation error of the battery is less than 3% during battery aging and temperature changes under complex working conditions. Moreover, the proposed method has only 1% of the computational burden of traditional methods, making it suitable for online applications.
JOURNAL OF SOLID STATE ELECTROCHEMISTRY
(2023)
Article
Energy & Fuels
Mina Ma, Xiaoyu Li, Wei Gao, Jinhua Sun, Qingsong Wang, Chris Mi
Summary: This study proposes a multi-fault diagnosis strategy focusing on detecting and isolating different types of faults in lithium-ion batteries. By using principal component analysis (PCA) and parallel kernel principal component analysis (KPCA), the method accurately detects faults and reconstructs fault waveforms to improve fault diagnosis reliability, as verified by tested data.
Article
Energy & Fuels
Guan Wang, Bei Jin, Mingzhu Wang, Yuedong Sun, Yuejiu Zheng, Teng Su
Summary: A novel state estimation method for hybrid battery packs is proposed in this study. The method utilizes the easy-to-estimate NMC battery to estimate the SOC of the LFP battery, and achieves continuous feedback correction through the design of a difference state observer. The method shows excellent estimation accuracy and robustness.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Engineering, Chemical
Huixin Tian, Jianhua Chen
Summary: Accurate estimation of SOC is crucial for vehicle management systems. This paper introduces an attention-based CONV-LSTM module for SOC prediction, based on CNN and LSTM networks, which shows promising results in experiments.
Article
Energy & Fuels
Ran Pang, Caizhi Zhang, Haifeng Dai, Yunfeng Bai, Dong Hao, Jinrui Chen, Bin Zhang
Summary: This study focuses on recognizing the health state of proton exchange membrane fuel cells by considering operating parameters, with the aim of improving the efficiency of health management in fuel cell vehicles. By using a combination of non-parametric statistics, unsupervised learning, and feature selection methods, the study successfully identifies key features leading to better health recognition and achieves a high accuracy rate of 95.04% using the random forest algorithm. Additionally, the effectiveness of the proposed method is validated through dynamic loading experiments under various operating conditions.
Article
Energy & Fuels
Qianqian Wang, Fumin Tang, Bing Li, Haifeng Dai, Jim P. Zheng, Cunman Zhang, Pingwen Ming
Summary: In this study, a new fuel cell model was established to investigate the thermal response of the proton exchange membrane fuel cell. The impacts of interface resistance, working conditions, and assembly pressure on thermal responses were systematically studied. It was found that the thermal contact resistance significantly increased the temperature in both regions, while the electrical contact resistance only slightly raised it. Additionally, uneven distribution and rapid overshoot/undershoot of temperature were observed during overload and change load operations. Choosing the appropriate assembly pressure was crucial for balancing performance and heat transfer.
Article
Energy & Fuels
Lei Zhao, Haifeng Dai, Fenglai Pei, Pingwen Ming, Xuezhe Wei, Jiangdong Zhou
Summary: This study selected four equivalent circuit models and compared and analyzed their differences in fitting results for electrochemical impedance spectroscopy under different working conditions. The results showed that the model with the Warburg element had the best fitting accuracy. Choosing the appropriate model based on different working conditions can provide better fitting for electrochemical impedance spectroscopy.
Article
Thermodynamics
Xin Lai, Yunfeng Huang, Huanghui Gu, Xuebing Han, Xuning Feng, Haifeng Dai, Yuejiu Zheng, Minggao Ouyang
Summary: The study proposes an RDE estimation method based on future load prediction, using HMM to predict battery future load, conducting capacity tests at different temperatures, and updating battery model parameters online using the FFRLS algorithm to improve accuracy and robustness.
Article
Thermodynamics
Siqi Chen, Guangxu Zhang, Changjun Wu, Wensheng Huang, Chengshan Xu, Changyong Jin, Yu Wu, Zhao Jiang, Haifeng Dai, Xuning Feng, Xuezhe Wei, Minggao Ouyang
Summary: This study proposes a design of a double-direction liquid heating-based battery module combined with the chassis for electric vehicles in an extremely low-temperature environment. Numerical calculations show that the proposed system is more efficient than commonly used battery thermal management systems, and an optimal design is obtained through multi-objective optimization. The study also guides the integration of efficient thermal management systems with vehicle chassis to improve thermal management efficiency and energy density under various climate conditions.
INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER
(2022)
Article
Chemistry, Physical
Guangxu Zhang, Xuezhe Wei, Siqi Chen, Jiangong Zhu, Guangshuai Han, Haifeng Dai
Summary: Shallow over-discharge has a significant impact on cell performance and thermal safety, primarily through the degradation of solid electrolyte interface film, copper plating, and shedding of active materials. As the depth of over-discharge deepens, the cell capacity decreases, resistance increases, heat generation becomes more significant, and thermal stability decreases. Additionally, the maximum temperature of the over-discharged cell is lower than that of a fresh cell.
JOURNAL OF POWER SOURCES
(2022)
Article
Engineering, Environmental
Qianqian Wang, Fumin Tang, Bing Li, Haifeng Dai, Jim P. Zheng, Cunman Zhang, Pingwen Ming
Summary: In this study, the thermal transient of the cathode catalyst layer (CCL) inside the proton exchange membrane fuel cell (PEMFC) under dynamic loading was investigated. The effects of current load, operating temperature, and channel to rib width ratio on the CCL temperature were systematically studied. It was found that there is an overshoot phenomenon in the CCL temperature when the current rapidly changes. This overshoot amplitude first increases and then decreases with the rise of the step current density. The loading time and operating temperature also have significant effects on the temperature overshoot. Additionally, the channel to rib width ratio affects the temperature fluctuation in different CCL regions.
CHEMICAL ENGINEERING JOURNAL
(2022)
Article
Thermodynamics
Dongdong Qiao, Xueyuan Wang, Xin Lai, Yuejiu Zheng, Xuezhe Wei, Haifeng Dai
Summary: A novel internal short circuit (ISC) diagnosis method based on incremental capacity (IC) curves is proposed in this study. The feasibility and effectiveness of the method are verified through experiments in a real electric vehicle working environment.
Article
Automation & Control Systems
Yuejiu Zheng, Qi Luo, Yifan Cui, Haifeng Dai, Xuebing Han, Xuning Feng
Summary: This article proposes a fault identification method based on capacity estimation, which can effectively distinguish micro-short circuit and low-capacity battery faults, and quantitatively estimate their capacities.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2022)
Article
Engineering, Electrical & Electronic
Bo Jiang, Haifeng Dai, Xuezhe Wei
Summary: This study investigates a novel cell-to-pack state estimation extension method based on a multilayer difference model (MDM) to address the challenges of battery degradation and cell inconsistency in existing state estimation methods. The proposed method efficiently realizes accurate estimation of State-of-Charge (SOC) and capacity for series-connected battery packs. Experimental results demonstrate the accuracy, efficiency, and adaptability of the proposed method under different dynamic conditions and various battery temperatures and cell inconsistencies.
IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION
(2022)
Article
Thermodynamics
Renzheng Li, Hui Wang, Haifeng Dai, Jichao Hong, Guangyao Tong, Xinbo Chen
Summary: This paper proposes a novel multi-step SOC prediction method using gated recurrent unit recurrent neural networks, considering the influences of the environment and driving behaviors. The method includes dual-dropout to prevent overfitting and optimize training efficiency. Real-world vehicle parameters are used as inputs. The method is validated and shown to achieve accurate real-time SOC prediction.
Article
Engineering, Electrical & Electronic
Xueyuan Wang, Yao Kou, Bin Wang, Zhao Jiang, Xuezhe Wei, Haifeng Dai
Summary: This article proposes a fast calculation method based on the S transform for obtaining broadband battery impedance. By processing the step disturbance and response generated by a common charging/discharging device, the method reduces the requirements for impedance acquisition and improves calculation efficiency. The experimental results show that the method has high accuracy within the error range of both the real and imaginary parts, and can save a significant amount of time compared to traditional methods.
IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION
(2022)
Article
Automation & Control Systems
Zhichao Luo, Yiyan Zhao, Meng Xiong, Xuezhe Wei, Haifeng Dai
Summary: This article proposes a self-tuning LCC/LCC wireless power transfer system based on switch-controlled capacitors, which can maintain a high power factor and fixed output power in the presence of self or mutual inductance variation. Experimental results demonstrate that the system is effective in maintaining high power factor and desired DC output power under different magnetic shielding materials.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2023)
Article
Transportation Science & Technology
Siqi Chen, Guangxu Zhang, Dongdong Qiao, Xueyuan Wang, Bo Jiang, Haifeng Dai, Jiangong Zhu, Xuezhe Wei
Summary: This study proposes a hybrid phase change material-liquid coolant-based battery thermal management system (BTMS) design using an artificial neural network (ANN) regression method to ensure the thermal performance and lifespan of a Li-ion battery module under fast charging. The accuracy of the regression models is validated through experimental data, and the predicted cooling effect matches well with the experimental results, indicating the accuracy and reliability of the ANN regression models.
SAE INTERNATIONAL JOURNAL OF ELECTRIFIED VEHICLES
(2022)
Article
Thermodynamics
Siqi Chen, Guangxu Zhang, Jiangong Zhu, Xuning Feng, Xuezhe Wei, Minggao Ouyang, Haifeng Dai
Summary: This study proposes a parallel liquid cooling system for fast charging of prismatic battery modules to achieve the shortest charging interval and thermal safety. Sensitivity analysis and response surface analysis are conducted to explore the impact of design parameters, and a multi-objective optimization design is performed. Experimental validation shows that the optimal design improves cooling effect, temperature uniformity, and energy cost.
APPLIED THERMAL ENGINEERING
(2022)
