Article
Chemistry, Physical
Nikolaos Wassiliadis, Johannes Kriegler, Kareem Abo Gamra, Markus Lienkamp
Summary: The increasing sales of battery electric vehicles have led to their wider use under demanding conditions, such as frequent fast charging and operation under low temperatures. To prevent battery aging and failure, a health-aware fast charging strategy based on a model of reduced order is proposed, which can significantly reduce charging time while prolonging the cycle life of lithium-ion batteries.
JOURNAL OF POWER SOURCES
(2023)
Review
Engineering, Electrical & Electronic
Cuili Chen, Zhongbao Wei, Alois Christian Knoll
Summary: This article provides a comprehensive review of existing charging optimization techniques for lithium-ion batteries, addressing the challenges of long charging time and degradation caused by fast charging. It discusses the operation and models of lithium-ion batteries and scrutinizes the side effects of unregulated fast charging on battery aging mechanism. The state-of-the-art open- and close-loop charging optimization techniques are systematically reviewed, highlighting their respective merits and shortcomings. The future development of a charging control protocol with real-time affordability and degradation consciousness is also discussed.
IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION
(2022)
Review
Energy & Fuels
Siyan Chen, Zhenhai Gao, Tianjun Sun
Summary: This review discusses the general working mechanism of Lithium-ion batteries, the thermal runaway process, trigger conditions, material factors, and advancements in battery safety. It aims to provide a general picture of thermal runaway risks and solutions for safer battery designs.
ENERGY SCIENCE & ENGINEERING
(2021)
Article
Chemistry, Physical
Teng Liu, Shanhai Ge, Xiao-Guang Yang, Chao-Yang Wang
Summary: This study suggests that allowing Li-ion batteries to charge at higher temperatures can alleviate the issues of increased cost and weight caused by strong cooling systems during fast charging. By using an experimentally validated model, it is shown that a gradually increasing temperature profile can achieve a balance between fast charging and thermal management of the battery.
JOURNAL OF POWER SOURCES
(2021)
Article
Energy & Fuels
Sagar Vashisht, Dibakar Rakshit, Satyam Panchal, Michael Fowler, Roydon Fraser
Summary: The current paper presents a two-dimensional electrothermal model that evaluates the thermal and voltage behaviour of a LiFePO4-20 Ah Li-ion pouch cell. The electrothermal model considers the impact of depth of discharge (DoD) and temperature on heat generated inside Li-ion cells by precisely simulating the internal equivalent resistance and entropy change utilizing experimental data. Overall, the simulated results obtained from the proposed electrothermal model exhibit similar trends and high accuracy when compared to the experimental data.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Energy & Fuels
Dario Pelosi, Michela Longo, Dario Zaninelli, Linda Barelli
Summary: A significant increase in fast-charging stations is crucial for the transition to electric vehicles. However, charging a battery pack at a higher C-rate accelerates its degradation. This paper proposes an innovative approach that considers the daily routine of an EV Li-ion battery based on a standard driving cycle, enabling the determination of the state of charge evolution for different charging C-rates. It demonstrates that fast-charging at 50 kW reduces battery lifespan by approximately 17% compared to charging in a 22 kW three-phase AC column.
Review
Engineering, Electrical & Electronic
Dawei Zhang, Chen Zhong, Peijuan Xu, Yiyang Tian
Summary: This study reviews the application of deep learning in the estimation of State of Charge (SOC) for lithium batteries in electric vehicles. It analyzes the technical process, datasets, neural networks, and the advantages and disadvantages of deep learning methods for SOC estimation. The study also discusses the selection of deep learning structures for SOC estimation and highlights the challenges and future directions in this field.
Article
Energy & Fuels
Praveen Nambisan, Pankaj Saha, Munmun Khanra
Summary: In this work, a real-time optimal fast charging protocol is implemented using Pontryagin's Minimum Principle (PMP) to solve the optimal control framework balancing between charging time and ohmic heat generation. The control concepts of costate jump conditions are modified and extensive offline optimization results are used to examine the real-time optimal fast charging protocol under varying operating constraints. The effect of different boundary conditions on charging profile and sensitive parameters, as well as comparison with a standard CCCV charging algorithm, is investigated. Finally, the comparison between a typical optimal fast charging profile and a standard 2C CCCV protocol is experimentally examined.
JOURNAL OF ENERGY STORAGE
(2021)
Article
Energy & Fuels
Kirandeep Kaur, Akhil Garg, Xujian Cui, Surinder Singh, Bijaya Ketan Panigrahi
Summary: By utilizing data-driven modeling with measurable battery signals, this study introduced the use of deep neural networks for battery capacity estimation. The results demonstrate that the LSTM model outperforms others in accuracy, and battery temperature has a relatively minor impact on capacity estimation.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
(2021)
Review
Thermodynamics
Xinghui Zhang, Zhao Li, Lingai Luo, Yilin Fan, Zhengyu Du
Summary: Electric vehicles powered by lithium-ion batteries have great potential in alleviating energy and environmental issues, but temperature management is crucial for their development and propagation. Both high and low temperature environments can negatively impact battery performance and safety, requiring proper handling.
Article
Chemistry, Multidisciplinary
Xu Jin, Yehu Han, Zhengfeng Zhang, Yawei Chen, Jianming Li, Tingting Yang, Xiaoqi Wang, Wanxia Li, Xiao Han, Zelin Wang, Xiaodan Liu, Hang Jiao, Xiaoxing Ke, Manling Sui, Ruiguo Cao, Genqiang Zhang, Yongfu Tang, Pengfei Yan, Shuhong Jiao
Summary: This study reports on the exceptional fast charge/discharge performance and long-term stability of a mesoporous single-crystalline lithium titanate (MSC-LTO) microrod in lithium-ion batteries (LIBs). The microrods exhibit high rate capability and minimal structure degradation, providing a new approach for developing fast-charging materials for LIBs.
ADVANCED MATERIALS
(2022)
Review
Energy & Fuels
Nikolaos Wassiliadis, Jakob Schneider, Alexander Frank, Leo Wildfeuer, Xue Lin, Andreas Jossen, Markus Lienkamp
Summary: Despite rapid technological progress, widespread adoption of battery electric vehicles (BEVs) is hindered by limited driving ranges and long charging times. Efforts to reduce charging times to 15 minutes, similar to refueling times for conventional vehicles, face challenges such as accelerated battery aging and safety hazards during operation. Various approaches have been explored to develop fast charging strategies for battery management systems, but consensus on the optimal solution remains elusive. This review evaluates over 50 studies on fast charging strategy determination, analyzing them based on parameterization efforts, battery types studied, and real-world applicability, to identify research gaps and enable transfer to electric vehicle applications.
JOURNAL OF ENERGY STORAGE
(2021)
Article
Energy & Fuels
Abdelilah Hammou, Raffaele Petrone, Demba Diallo, Hamid Gualous
Summary: This work proposes a method to estimate the capacity and direct current internal resistance of Li-ion batteries using already available current and voltage measurements. The estimations are validated with experimental measurements, showing a mean relative error lower than 5% for the direct current internal resistance and lower than 2% for the capacity estimation. The method is simple and suitable for embedded battery monitoring as it uses already available voltage and current measurements.
IEEE TRANSACTIONS ON ENERGY CONVERSION
(2023)
Article
Energy & Fuels
Mohammed Al-Saadi, Josu Olmos, Andoni Saez-de-Ibarra, Joeri Van Mierlo, Maitane Berecibar
Summary: Fast charging is crucial for the wider adoption of Electric Vehicles (EVs), but it can lead to degradation of Li-ion Batteries (LIBs), making it essential to understand how fast charging affects battery degradation in order to design appropriate infrastructure and powertrains. Research on Battery Electric Buses (BEBs) in European cities found that reducing charger size and increasing battery capacity are cost-effective measures to mitigate LIB degradation during fast charging processes.
Article
Chemistry, Physical
Duanmei Song, Jiadong Yu, Mengmeng Wang, Quanyin Tan, Kang Liu, Jinhui Li
Summary: The critical supply of materials for lithium-ion batteries (LIBs) has become highly vulnerable to epidemics and geopolitical influences, highlighting the importance of independent and autonomous in situ recycling of LIBs. Many technologies have been developed rapidly for recycling spent LIBs in the last decade. However, their sustainability is seriously questioned, given the blind pursuit of recycling efficiency and profit maximization, even if the so-called innovative methods.
ENERGY STORAGE MATERIALS
(2023)
Article
Thermodynamics
Fengqi Zhang, Lehua Xiao, Serdar Coskun, Hui Pang, Shaobo Xie, Kailong Liu, Yahui Cui
Summary: This article presents a comprehensive comparative study of energy management strategies (EMSs) for a parallel hybrid electric vehicle (HEV) considering battery ageing. The principles of dynamic programming (DP), Pontryagin's minimum principle (PMP), and equivalent consumption minimization strategy (ECMS) with battery ageing are elaborated. A gearshift map is obtained from DP optimization results to optimize drivability and fuel economy, and it is applied in the PMP and ECMS. Fuel economy, battery state-of-charge charge-sustainability, and computational efficiency are compared for different EMSs. Battery ageing is also included in the optimization solution using a control-oriented model. DP achieves the best fuel economy compared to other methods, with about a 2% difference in fuel economy compared to PMP. The analysis results provide valuable insights into the advantages and disadvantages of each approach.
Article
Automation & Control Systems
Tianyu Hu, Huimin Ma, Kailong Liu, Hongbin Sun
Summary: In this article, a knowledge-data-driven attention model (CFKDA) is proposed for Li-ion battery calendar health prognostics. By combining domain knowledge and data, CFKDA has demonstrated improved theoretical strength and prognostic performance. Experimental results show the superiority of CFKDA in forecasting and generalizing to unwitnessed conditions over state-of-the-art models.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2023)
Article
Engineering, Electrical & Electronic
Wei Li, Yi Xie, Kailong Liu, Rui Yang, Bin Chen, Yangjun Zhang
Summary: This article proposes an enhanced thermal model for pouch batteries, which can be used for battery management systems in low temperature and high current conditions. The model integrates a virtual resistance model (VRM) and a post resistance model for low temperatures. The VRM is extrapolated from the resistance model under room temperature conditions based on the Arrhenius equation. The complete thermal model is validated at low temperatures and high discharge rates, with maximum mean errors of 0.72°C for cyclic pulse current and 0.79°C for constant current working conditions.
IEEE JOURNAL OF EMERGING AND SELECTED TOPICS IN POWER ELECTRONICS
(2023)
Article
Engineering, Electrical & Electronic
Chong Zhu, Jingbo Han, Hua Zhang, Fei Lu, Kailong Liu, Xi Zhang
Summary: To solve the degradation of lithium-ion batteries in cold climates, researchers have developed an integrated battery self-heater based on traction motor drive topology reconfiguration. This eliminates the need for additional hardware and effectively preheats automotive batteries.
IEEE JOURNAL OF EMERGING AND SELECTED TOPICS IN POWER ELECTRONICS
(2023)
Article
Engineering, Electrical & Electronic
Tianyu Hu, Huimin Ma, Hongbin Sun, Kailong Liu
Summary: In this article, a generative adversarial network-based (GAN-based) model called Capacit Forecast GAN (CFGAN) is proposed for the forecast of battery calendar aging. CFGAN utilizes electrochemical knowledge to design its crucial part, the conditioner, to maintain consistency between knowledge and data, improving its theoretical strength and forecast performance significantly. Results from practical case studies demonstrate the superiority of CFGAN in forecasting and generalization to unseen conditions, indicating its ability to capture the complex multimodality of the condition-varying calendar aging process.
IEEE JOURNAL OF EMERGING AND SELECTED TOPICS IN POWER ELECTRONICS
(2023)
Letter
Automation & Control Systems
Kailong Liu, Qiao Peng, Remus Teodorescu, Aoife M. Foley
Summary: This letter presents an effective battery calendar ageing trajectory prediction model based on support vector regression (SVR) technology, which combines the mechanism and empirical knowledge elements of battery storage temperature, state-of-charge (SoC), and time. The model achieves highly accurate predictions for witnessed conditions and also demonstrates good generalization ability for unwitnessed conditions, reducing the required experimental time and cost.
IEEE-CAA JOURNAL OF AUTOMATICA SINICA
(2023)
Editorial Material
Automation & Control Systems
Kailong Liu, Yujie Wang, Weixiang Shen, Zhongbao Wei, Chunhui Zhao, Huazhen Fang
CONTROL ENGINEERING PRACTICE
(2023)
Article
Automation & Control Systems
Yi Xie, Wei Li, Xiaosong Hu, Manh-Kien Tran, Satyam Panchal, Michael Fowler, Yangjun Zhang, Kailong Liu
Summary: This article proposes a distributed spatial-temporal online correction algorithm for the coestimation of the state of charge (SOC) and state of temperature (SOT) of batteries, which is crucial for a battery management system in achieving a green industrial economy. The algorithm identifies the internal resistance and estimates SOC using an adaptive Kalman filter. It then couples SOC estimation with an online restoration algorithm for distributed temperature, using an improved fractal growth process. The proposed coestimation algorithm improves SOC estimation fidelity by up to 1.5% and maintains the mean relative error of SOT estimation within 8%.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2023)
Article
Engineering, Electrical & Electronic
Wei Li, Yi Xie, Xiaosong Hu, Manh-Kien Tran, Michael Fowler, Satyam Panchal, Jintao Zheng, Kailong Liu
Summary: AC pulse heating is a low-energy and high-efficiency preheating method for lithium-ion batteries. In this study, a dual RC model and a thermal model were used to predict the battery temperature and negative electrode potential. The upper bound of heating current (UBHC) was determined by the criteria of negative electrode potential reaching 0 V, indicating lithium plating. The proposed self-adaptive AC pulse heating strategy improved the heating efficiency compared to constant amplitude pulse heating.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Computer Science, Artificial Intelligence
Lingxing Kong, Kailong Liu, Deyi Fu, Boyong Liu, Jingkai Ma, Huini Sun, Shuang Bai
Summary: Accurately evaluating the technological improvement effects of wind turbines is crucial for wind farm operators. This paper proposes an innovative approach that employs a wind power regression model which leverages external environmental information to predict the output power of wind turbines. The proposed model, stacked LSTM networks with attention mechanisms, enhances the nonlinear fitting ability and captures deeper features of the input sequence. The experiments show that the proposed method outperforms various wind power prediction benchmarks.
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
(2023)
Article
Engineering, Electrical & Electronic
Huang Zhang, Yang Su, Faisal Altaf, Torsten Wik, Sebastien Gros
Summary: Battery cycle life prediction using early degradation data has many potential applications throughout the battery product life cycle. However, predicting cycle life with quantified uncertainty is still lacking and the interpretability of advanced data-driven methods needs investigation.
IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION
(2023)
Article
Energy & Fuels
Kailong Liu, Qiao Peng, Yunhong Chec, Yusheng Zheng, Kang Lid, Remus Teodorescuc, Dhammika Widanage, Anup Barai
Summary: This paper presents a systematic review on the applications of transfer learning in the field of battery management, with particular focuses on battery state estimation and ageing prognostics. Transfer learning can offer potential solutions to the issues faced by conventional battery management by transferring existing knowledge from different but related domains. The state of the art in terms of principles, algorithm frameworks, advantages and disadvantages are discussed, followed by a discussion on future trends of data-driven battery management with transfer learning.
ADVANCES IN APPLIED ENERGY
(2023)
Article
Engineering, Electrical & Electronic
Guang Wang, Gaofeng Zhao, Jiale Xie, Kailong Liu
Summary: This article proposes an improved correlation coefficient method for multifault diagnosis of battery packs in electric vehicles. It utilizes multivariate statistical analysis and Bayesian probability theory under the framework of ensemble learning. The method creates local submodels based on cross-cell voltage correlation signals and implements fault diagnosis using independent component analysis. Results are integrated using Bayesian probabilistic ensemble interface, and accurate fault type identification and localization are achieved using ensemble fault probability and ensemble contribution rate.
IEEE TRANSACTIONS ON POWER ELECTRONICS
(2023)
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
Xin Gu, Jinglun Li, Kailong Liu, Yuhao Zhu, Xuewen Tao, Yunlong Shang
Summary: This study presents a minor fault diagnosis approach for lithium-ion batteries based on phase plane sample entropy, which accurately detects minor faults and predicts the time of occurrence. Experimental results demonstrate the effectiveness, robustness, and generalizability of the proposed method.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2023)
