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Xiaosong Hu

Also published under: Xiao-Song Hu, X. Hu

Publications
135
Citations
11,090
Publications by Year
20142025
Co-Authors:
Show All Co-Authors (241)
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Xiaosong Hu

Also published under: Xiao-Song Hu, X. Hu

Affiliation

Department of Mechanical and Vehicle Engineering
Chongqing University
Chongqing, China

Publication Topics

Biography

Xiaosong Hu (xiaosonghu@cqu.edu.cn) is a professor with the Department of Mechanical and Vehicle Engineering, Chongqing University, China.(Based on document published on 11 March 2022).
Publications
135
Citations
11,090
Publications by Year
20142025
Co-Authors:
Show All Co-Authors (241)
Author's Published Works

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Co-optimized Analytical Solution of Speed Planning and Energy Management for Automated Hybrid Electric Vehicles under Multi-Signal Intersections Scenario

Fengqi Zhang;Lehua Xiao;Shaobo Xie;Serdar Coskun;Yingshi Guo;Yalian Yang;Xiaosong Hu

IEEE Transactions on Transportation Electrification
Year: 2025 | Early Access Article |
Eco-driving is a viable technology with higher energy-saving potential at signalized intersections. The rapid development of connected and automated technology provides more opportunities for the eco-driving of hybrid electric vehicles (HEVs). However, it is more challenging to co-optimize speed planning and energy management due to their coupling and complex features. To this end, a co-optimizati...Show More

Co-optimized Analytical Solution of Speed Planning and Energy Management for Automated Hybrid Electric Vehicles under Multi-Signal Intersections Scenario

Fengqi Zhang;Lehua Xiao;Shaobo Xie;Serdar Coskun;Yingshi Guo;Yalian Yang;Xiaosong Hu

Year: 2025 | Early Access Article |

Experience-Shared Variable-Step Predictive Control of Range-Extended Electric Vehicles Using Transferable Driver Model

Ji Li;Zirui Li;Chengqing Wen;Yanhong Wu;Roger Dixon;Xiaosong Hu;Hongming Xu

IEEE Transactions on Intelligent Transportation Systems
Year: 2025 | Volume: 26, Issue: 1 | Journal Article |
Integrating range-extended electric vehicles (REEVs) in the automotive market is a key part of the drive toward environmental sustainability. This paper leverages an experience-shared approach to variable-step predictive control to improve REEV energy efficiency, where a transferable driver model is designed to accommodate varying driver experience levels via knowledge transfer. This model incorpo...Show More

Experience-Shared Variable-Step Predictive Control of Range-Extended Electric Vehicles Using Transferable Driver Model

Ji Li;Zirui Li;Chengqing Wen;Yanhong Wu;Roger Dixon;Xiaosong Hu;Hongming Xu

Year: 2025 | Volume: 26, Issue: 1 | Journal Article |

Bias-Compensated State of Charge and State of Health Joint Estimation for Lithium Iron Phosphate Batteries

Baozhao Yi;Xinhao Du;Jiawei Zhang;Xiaogang Wu;Qiuhao Hu;Weiran Jiang;Xiaosong Hu;Ziyou Song

IEEE Transactions on Power Electronics
Year: 2025 | Volume: 40, Issue: 2 | Journal Article |
Cited by: Papers (2)
Accurate estimation of the state of charge (SOC) and state of health (SOH) is crucial for safe and reliable operation of batteries. Voltage measurement bias strongly affects state estimation accuracy, especially in Lithium Iron Phosphate (LFP) batteries, owing to the flat open-circuit voltage (OCV) curves. This work introduces a bias-compensated algorithm to reliably estimate SOC and SOH of LFP ba...Show More

Bias-Compensated State of Charge and State of Health Joint Estimation for Lithium Iron Phosphate Batteries

Baozhao Yi;Xinhao Du;Jiawei Zhang;Xiaogang Wu;Qiuhao Hu;Weiran Jiang;Xiaosong Hu;Ziyou Song

Year: 2025 | Volume: 40, Issue: 2 | Journal Article |

A Data-Driven Method for Health Monitoring of Lithium-Ion Batteries in Real-World Scenarios

Jinwen Li;Zhongwei Deng;Xiaosong Hu

2024 IEEE Transportation Electrification Conference and Expo, Asia-Pacific (ITEC Asia-Pacific)
Year: 2024 | Conference Paper |
Accurate and efficient monitoring of the state of health (SOH) of lithium-ion batteries during operation is the key to ensure the safe and reliable operation of electric vehicles (EVs). However, applying existing lab-based methods directly to field data is challenging due to the complex operating conditions in realistic scenarios. Therefore, this study introduces a data-driven SOH estimation metho...Show More

A Data-Driven Method for Health Monitoring of Lithium-Ion Batteries in Real-World Scenarios

Jinwen Li;Zhongwei Deng;Xiaosong Hu

Year: 2024 | Conference Paper |

Comparative Analysis of Control Observer-Based Methods for State Estimation of Lithium-Ion Batteries in Practical Scenarios

Muhammad Saeed;Arash Khalatbarisoltani;Zhongwei Deng;Wenxue Liu;Faisal Altaf;Shuai Lu;Xiaosong Hu

IEEE/ASME Transactions on Mechatronics
Year: 2024 | Early Access Article |
Cited by: Papers (2)
The reliability, lower computational complexity, and ease of implementation of control observers make them one of the most promising methods for the state estimation of Li-ion batteries (LIBs) in commercial applications. To pave their way, this study performs a comprehensive and systematic evaluation of four main categories of control observer-based methods in different practical scenarios conside...Show More

Comparative Analysis of Control Observer-Based Methods for State Estimation of Lithium-Ion Batteries in Practical Scenarios

Muhammad Saeed;Arash Khalatbarisoltani;Zhongwei Deng;Wenxue Liu;Faisal Altaf;Shuai Lu;Xiaosong Hu

Year: 2024 | Early Access Article |

Thermal Monitoring and Multi-state Estimation of Li-ion Batteries Using a Control-oriented Integrated Electrothermal Framework

Muhammad Saeed;Hassan Abbas Khan;Qadeer Ahmed;Muhammad Rizwan Azam;Hafiz Muhammad Jawaad;Shuai Lu;Arash Khalatbarisoltani;Xiaosong Hu

2024 IEEE Workshop on Control and Modeling for Power Electronics (COMPEL)
Year: 2024 | Conference Paper |
Cited by: Papers (2)
We propose an integrated design for the combined estimation of state-modified cell core temperature, temperature-corrected state of charge (SOC), and state of energy (SOE) of lithium-ion batteries (LIBs). First, a control-oriented integrated electrothermal coupled model is constructed. The observability of the proposed MIMO system is rigorously investigated, and an adaptive PI observer is formulat...Show More

Thermal Monitoring and Multi-state Estimation of Li-ion Batteries Using a Control-oriented Integrated Electrothermal Framework

Muhammad Saeed;Hassan Abbas Khan;Qadeer Ahmed;Muhammad Rizwan Azam;Hafiz Muhammad Jawaad;Shuai Lu;Arash Khalatbarisoltani;Xiaosong Hu

Year: 2024 | Conference Paper |

Integrated Framework for Accurate State Estimation of Lithium-Ion Batteries Subject to Measurement Uncertainties

Muhammad Saeed;Shuai Lu;Ziyou Song;Xiaosong Hu

IEEE Transactions on Power Electronics
Year: 2024 | Volume: 39, Issue: 7 | Journal Article |
Cited by: Papers (4)
The effectiveness of a battery management system (BMS) in lithium-ion batteries (LIBs) is significantly dependent on the accuracy of battery sensors. However, owing to the highly nonlinear nature of LIBs, detecting small uncertainties in sensor measurements, which can lead to high estimation errors, poses a remarkable challenge. Moreover, in conventional BMS, sensor uncertainty detection and state...Show More

Integrated Framework for Accurate State Estimation of Lithium-Ion Batteries Subject to Measurement Uncertainties

Muhammad Saeed;Shuai Lu;Ziyou Song;Xiaosong Hu

Year: 2024 | Volume: 39, Issue: 7 | Journal Article |

Enhanced Electrothermal State Estimation and Experimental Validations for Electric Flying Car Batteries

Wenxue Liu;Yusheng Zheng;Arash Khalatbarisoltani;Le Xu;Yongjun Pan;Xiaosong Hu

IEEE/ASME Transactions on Mechatronics
Year: 2024 | Volume: 29, Issue: 6 | Journal Article |
Urban air mobility (UAM) has become an emerging urban travel paradigm due to its viability of alleviating traffic congestion and reducing commute time. Accurate and robust knowledge of key battery states, such as state of charge (SOC), state of temperature (SOT), and state of power (SOP), is a prerequisite for the safe, efficient, and reliable operation of electric flying cars. In this article, we...Show More

Enhanced Electrothermal State Estimation and Experimental Validations for Electric Flying Car Batteries

Wenxue Liu;Yusheng Zheng;Arash Khalatbarisoltani;Le Xu;Yongjun Pan;Xiaosong Hu

Year: 2024 | Volume: 29, Issue: 6 | Journal Article |

Online Sensorless Temperature Estimation of Lithium-Ion Batteries Through Electro-Thermal Coupling

Yusheng Zheng;Yunhong Che;Xiaosong Hu;Xin Sui;Remus Teodorescu

IEEE/ASME Transactions on Mechatronics
Year: 2024 | Volume: 29, Issue: 6 | Journal Article |
Cited by: Papers (3)
Owing to the nonnegligible impacts of temperature on the safety, performance, and lifespan of lithium-ion batteries, it is essential to regulate battery temperature to an optimal range. Temperature monitoring plays a fundamental role in battery thermal management, yet it is still challenged by limited onboard temperature sensors, particularly in large-scale battery applications. As such, developin...Show More

Online Sensorless Temperature Estimation of Lithium-Ion Batteries Through Electro-Thermal Coupling

Yusheng Zheng;Yunhong Che;Xiaosong Hu;Xin Sui;Remus Teodorescu

Year: 2024 | Volume: 29, Issue: 6 | Journal Article |

Degradation Pattern Recognition and Features Extrapolation for Battery Capacity Trajectory Prediction

Jinwen Li;Zhongwei Deng;Yunhong Che;Yi Xie;Xiaosong Hu;Remus Teodorescu

IEEE Transactions on Transportation Electrification
Year: 2024 | Volume: 10, Issue: 3 | Journal Article |
Cited by: Papers (2)
The successful integration of statistical machine learning techniques into battery health diagnosis has significantly advanced the development of transportation electrification. To achieve predictive maintenance of batteries, we propose a comprehensive data-driven approach for battery capacity trajectory prediction based on degradation pattern (DP) recognition and health indicators (HIs) extrapola...Show More

Degradation Pattern Recognition and Features Extrapolation for Battery Capacity Trajectory Prediction

Jinwen Li;Zhongwei Deng;Yunhong Che;Yi Xie;Xiaosong Hu;Remus Teodorescu

Year: 2024 | Volume: 10, Issue: 3 | Journal Article |

Traffic Information-Based Hierarchical Control Strategies for Eco-Driving of Plug-In Hybrid Electric Vehicles

Yapeng Li;Yalian Yang;Xianke Lin;Xiaosong Hu

IEEE Transactions on Vehicular Technology
Year: 2024 | Volume: 73, Issue: 3 | Journal Article |
Cited by: Papers (3)
The development of intelligent transportation technology provides a great opportunity for energy efficiency improvement of electrified vehicles. However, for plug-in hybrid vehicles, eco-driving control usually involves three problems, including speed planning, SOC planning, and energy management. Solving the above three problems requires considering not only the fuel economy but also the computat...Show More

Traffic Information-Based Hierarchical Control Strategies for Eco-Driving of Plug-In Hybrid Electric Vehicles

Yapeng Li;Yalian Yang;Xianke Lin;Xiaosong Hu

Year: 2024 | Volume: 73, Issue: 3 | Journal Article |

Energy Management in Plug-In Hybrid Electric Vehicles: Preheating the Battery Packs in Low-Temperature Driving Scenarios

Jie Han;Arash Khalatbarisoltani;Yalian Yang;Xiaosong Hu

IEEE Transactions on Intelligent Transportation Systems
Year: 2024 | Volume: 25, Issue: 2 | Journal Article |
Cited by: Papers (9)
Plug-in hybrid electric vehicles (PHEVs) with large battery packs have significant advantages in improving fuel efficiency and lowering harmful emissions. However, battery charging and discharging performance degrades dramatically at low temperatures, resulting in increasing vehicle operating expenses, which hinders the deployment of PHEVs in severe cold regions. To address this challenge, this pa...Show More

Energy Management in Plug-In Hybrid Electric Vehicles: Preheating the Battery Packs in Low-Temperature Driving Scenarios

Jie Han;Arash Khalatbarisoltani;Yalian Yang;Xiaosong Hu

Year: 2024 | Volume: 25, Issue: 2 | Journal Article |

Energy Management Strategies for Fuel Cell Vehicles: A Comprehensive Review of the Latest Progress in Modeling, Strategies, and Future Prospects

Arash Khalatbarisoltani;Haitao Zhou;Xiaolin Tang;Mohsen Kandidayeni;Loïc Boulon;Xiaosong Hu

IEEE Transactions on Intelligent Transportation Systems
Year: 2024 | Volume: 25, Issue: 1 | Journal Article |
Cited by: Papers (17)
Fuel cell vehicles (FCVs) are considered a promising solution for reducing emissions caused by the transportation sector. An energy management strategy (EMS) is undeniably essential in increasing hydrogen economy, component lifetime, and driving range. While the existing EMSs provide a range of performance levels, they suffer from significant shortcomings in robustness, durability, and adaptabilit...Show More

Energy Management Strategies for Fuel Cell Vehicles: A Comprehensive Review of the Latest Progress in Modeling, Strategies, and Future Prospects

Arash Khalatbarisoltani;Haitao Zhou;Xiaolin Tang;Mohsen Kandidayeni;Loïc Boulon;Xiaosong Hu

Year: 2024 | Volume: 25, Issue: 1 | Journal Article |

Hierarchical Control Strategies for Connected Heavy-Duty Modular Fuel Cell Vehicles via Decentralized Convex Optimization

Hao Long;Arash Khalatbarisoltani;Yalian Yang;Xiaosong Hu

IEEE Transactions on Vehicular Technology
Year: 2024 | Volume: 73, Issue: 1 | Journal Article |
Cited by: Papers (7)
Fuel cell vehicles (FCVs) are gaining popularity in heavy-duty transportation applications because of their high efficiency, lack of local emissions, and short refueling time. Moreover, cooperative adaptive cruise control (CACC), which plans the longitudinal movements of heavy-duty vehicles, is also a potential solution to increase fuel efficiency, safety, and road capacity. In order to integrate ...Show More

Hierarchical Control Strategies for Connected Heavy-Duty Modular Fuel Cell Vehicles via Decentralized Convex Optimization

Hao Long;Arash Khalatbarisoltani;Yalian Yang;Xiaosong Hu

Year: 2024 | Volume: 73, Issue: 1 | Journal Article |

Sensorless Temperature Monitoring of Lithium-Ion Batteries by Integrating Physics With Machine Learning

Yusheng Zheng;Yunhong Che;Xiaosong Hu;Xin Sui;Remus Teodorescu

IEEE Transactions on Transportation Electrification
Year: 2024 | Volume: 10, Issue: 2 | Journal Article |
Cited by: Papers (7)
The large-scale application of lithium-ion batteries (LIBs) in electric vehicles (EVs) requires meticulous battery management to guarantee vehicular safety and performance. Temperatures play a significant role in the safety, performance, and lifetime of LIBs. Therefore, the state of temperature (SOT) of batteries should be monitored timely by the battery management system. Due to limited onboard t...Show More

Sensorless Temperature Monitoring of Lithium-Ion Batteries by Integrating Physics With Machine Learning

Yusheng Zheng;Yunhong Che;Xiaosong Hu;Xin Sui;Remus Teodorescu

Year: 2024 | Volume: 10, Issue: 2 | Journal Article |

Fault Diagnosis of Electric City Bus High-Voltage Load System Based on Multidomain Sparse Representation

Xianglong You;Zhongwei Deng;Yalian Yang;Xianke Lin;Xiaosong Hu

IEEE Transactions on Transportation Electrification
Year: 2024 | Volume: 10, Issue: 1 | Journal Article |
Cited by: Papers (3)
This article presents a system-level fault diagnosis scheme for the high-voltage load system of electric city bus (ECB). First, a predesigned excitation signal generated by the battery system is injected into the high-voltage load system during parking, and the response signal is captured by high-speed data acquisition device. Then, time domain features, frequency domain features, and time-frequen...Show More

Fault Diagnosis of Electric City Bus High-Voltage Load System Based on Multidomain Sparse Representation

Xianglong You;Zhongwei Deng;Yalian Yang;Xianke Lin;Xiaosong Hu

Year: 2024 | Volume: 10, Issue: 1 | Journal Article |

Hierarchical Optimization of Speed Planning and Energy Management for Connected Hybrid Electric Vehicles Under Multi-Lane and Signal Lights Aware Scenarios

Jinghui Peng;Fengqi Zhang;Serdar Coskun;Xiaosong Hu;Yalian Yang;Reza Langari;Jinsong He

IEEE Transactions on Intelligent Transportation Systems
Year: 2023 | Volume: 24, Issue: 12 | Journal Article |
Cited by: Papers (4)
Connected and automated vehicle technology via vehicle-to-everything communication, can assist in improving energy efficiency for hybrid electric vehicles (HEVs). In particular, information about the timing of traffic lights and surrounding vehicles can be exchanged between traffic vehicles and in conjunction with vehicle state information, to improve the fuel economy of HEVs significantly. To thi...Show More

Hierarchical Optimization of Speed Planning and Energy Management for Connected Hybrid Electric Vehicles Under Multi-Lane and Signal Lights Aware Scenarios

Jinghui Peng;Fengqi Zhang;Serdar Coskun;Xiaosong Hu;Yalian Yang;Reza Langari;Jinsong He

Year: 2023 | Volume: 24, Issue: 12 | Journal Article |

Integrating Model Predictive Control With Federated Reinforcement Learning for Decentralized Energy Management of Fuel Cell Vehicles

Arash Khalatbarisoltani;Loïc Boulon;Xiaosong Hu

IEEE Transactions on Intelligent Transportation Systems
Year: 2023 | Volume: 24, Issue: 12 | Journal Article |
Cited by: Papers (17)
The optimization-based energy management strategy (EMS) enables expertise to improve the performance of fuel cell vehicles (FCVs). Ongoing efforts are mostly focused on optimizing a centralized EMS using a variety of high-computing technologies without offering appropriate scalability and modularity for the onboard powertrain components. In real-time applications, the time-accomplishment capabilit...Show More

Integrating Model Predictive Control With Federated Reinforcement Learning for Decentralized Energy Management of Fuel Cell Vehicles

Arash Khalatbarisoltani;Loïc Boulon;Xiaosong Hu

Year: 2023 | Volume: 24, Issue: 12 | Journal Article |

Stochastic Velocity Prediction for Connected Vehicles Considering V2V Communication Interruption

Lihua Wang;Fengqi Zhang;Yahui Cui;Serdar Coskun;Xiaolin Tang;Yalian Yang;Xiaosong Hu

IEEE Transactions on Intelligent Transportation Systems
Year: 2023 | Volume: 24, Issue: 11 | Journal Article |
Cited by: Papers (1)
Reliable and accurate velocity prediction can significantly contribute to the quality of connected vehicle control applications. Existing efforts focus on the velocity prediction without considering vehicle-to-vehicle (V2V) communication interruption. Hence, a stochastic velocity prediction method for connected vehicles considering V2V communication interruption is put forward for the first time. ...Show More

Stochastic Velocity Prediction for Connected Vehicles Considering V2V Communication Interruption

Lihua Wang;Fengqi Zhang;Yahui Cui;Serdar Coskun;Xiaolin Tang;Yalian Yang;Xiaosong Hu

Year: 2023 | Volume: 24, Issue: 11 | Journal Article |

Battery Aging Behavior Evaluation Under Variable and Constant Temperatures with Real Loading Profiles

Yunhong Che;Daniel-Ioan Stroe;Xin Sui;Sϕren Byg Vilsen;Xiaosong Hu;Remus Teodorescu

2023 IEEE Applied Power Electronics Conference and Exposition (APEC)
Year: 2023 | Conference Paper |
Studying and analyzing battery aging behavior is crucial in battery health prognostic and management. This paper conducts novel and comprehensive experiments to evaluate battery aging under variable external stresses, including different dynamic load profiles and variable environmental temperatures. Respond analysis in the time and frequency domain is performed to account for the different aging r...Show More

Battery Aging Behavior Evaluation Under Variable and Constant Temperatures with Real Loading Profiles

Yunhong Che;Daniel-Ioan Stroe;Xin Sui;Sϕren Byg Vilsen;Xiaosong Hu;Remus Teodorescu

Year: 2023 | Conference Paper |

Battery States Monitoring for Electric Vehicles Based on Transferred Multi-Task Learning

Yunhong Che;Yusheng Zheng;Yue Wu;Xianke Lin;Jiacheng Li;Xiaosong Hu;Remus Teodorescu

IEEE Transactions on Vehicular Technology
Year: 2023 | Volume: 72, Issue: 8 | Journal Article |
Cited by: Papers (10)
State/temperature monitoring is one of the key requirements of battery management systems that facilitates efficient and intelligent management to ensure the safe operation of batteries in electrified transportation. This paper proposes an online end-to-end state monitoring method based on transferred multi-task learning. Measurement data is directly used for sharing information generation with th...Show More

Battery States Monitoring for Electric Vehicles Based on Transferred Multi-Task Learning

Yunhong Che;Yusheng Zheng;Yue Wu;Xianke Lin;Jiacheng Li;Xiaosong Hu;Remus Teodorescu

Year: 2023 | Volume: 72, Issue: 8 | Journal Article |

Dynamic Traffic Prediction-Based Energy Management of Connected Plug-In Hybrid Electric Vehicles with Long Short-Term State of Charge Planning

Nan Zhao;Fengqi Zhang;Yalian Yang;Serdar Coskun;Xianke Lin;Xiaosong Hu

IEEE Transactions on Vehicular Technology
Year: 2023 | Volume: 72, Issue: 5 | Journal Article |
Cited by: Papers (9)
Vehicle electrification, automation, and connectivity in today's transportation require significant efforts in control design to meet conflicting goals of energy efficiency, traffic safety, as well as comfort. The rapid development of intelligent transportation systems (ITS) and the rapid growth of connectivity technologies enable vehicles to receive more information about traffic conditions, whic...Show More

Dynamic Traffic Prediction-Based Energy Management of Connected Plug-In Hybrid Electric Vehicles with Long Short-Term State of Charge Planning

Nan Zhao;Fengqi Zhang;Yalian Yang;Serdar Coskun;Xianke Lin;Xiaosong Hu

Year: 2023 | Volume: 72, Issue: 5 | Journal Article |

An Early Soft Internal Short-Circuit Fault Diagnosis Method for Lithium-Ion Battery Packs in Electric Vehicles

Kai Zhang;Lulu Jiang;Zhongwei Deng;Yi Xie;Jonathan Couture;Xianke Lin;Jingjing Zhou;Xiaosong Hu

IEEE/ASME Transactions on Mechatronics
Year: 2023 | Volume: 28, Issue: 2 | Journal Article |
Cited by: Papers (26)
The early detection of soft internal short-circuit faults in lithium-ion battery packs is critical to ensuring the safe and reliable operation of electric vehicles. This article proposes a fault diagnosis method that can achieve the detection and assessment of soft internal short-circuit faults for lithium-ion battery packs. Specifically, based on the incremental capacity curve, fault features are...Show More

An Early Soft Internal Short-Circuit Fault Diagnosis Method for Lithium-Ion Battery Packs in Electric Vehicles

Kai Zhang;Lulu Jiang;Zhongwei Deng;Yi Xie;Jonathan Couture;Xianke Lin;Jingjing Zhou;Xiaosong Hu

Year: 2023 | Volume: 28, Issue: 2 | Journal Article |

An Internal Heating Strategy for Lithium-Ion Batteries Without Lithium Plating Based on Self-Adaptive Alternating Current Pulse

Wei Li;Yi Xie;Xiaosong Hu;Manh-Kien Tran;Michael Fowler;Satyam Panchal;Jintao Zheng;Kailong Liu

IEEE Transactions on Vehicular Technology
Year: 2023 | Volume: 72, Issue: 5 | Journal Article |
Cited by: Papers (34)
AC pulse heating is a promising preheating method for lithium-ion batteries due to its low energy cost and high efficiency. To avoid the lithium plating in the AC heating, upper bound of heating current (UBHC) should be obtained. In this paper, the dual RC model is developed, and coupled with the thermal model to predict the battery temperature and potential of negative electrode (PNE). PNE = 0 V ...Show More

An Internal Heating Strategy for Lithium-Ion Batteries Without Lithium Plating Based on Self-Adaptive Alternating Current Pulse

Wei Li;Yi Xie;Xiaosong Hu;Manh-Kien Tran;Michael Fowler;Satyam Panchal;Jintao Zheng;Kailong Liu

Year: 2023 | Volume: 72, Issue: 5 | Journal Article |

A Novel Hybrid Physics-Based and Data-Driven Approach for Degradation Trajectory Prediction in Li-Ion Batteries

Le Xu;Zhongwei Deng;Yi Xie;Xianke Lin;Xiaosong Hu

IEEE Transactions on Transportation Electrification
Year: 2023 | Volume: 9, Issue: 2 | Journal Article |
Cited by: Papers (27)
Lithium-ion batteries have been widely used in electric vehicles. To ensure safety and reliability, accurate prediction of the battery’s future degradation trajectory is critical. However, early prediction capability and adaptive prediction capability under various battery aging conditions remain two main challenges. Either physics-based or data-driven methods have their advantages and limitations...Show More

A Novel Hybrid Physics-Based and Data-Driven Approach for Degradation Trajectory Prediction in Li-Ion Batteries

Le Xu;Zhongwei Deng;Yi Xie;Xianke Lin;Xiaosong Hu

Year: 2023 | Volume: 9, Issue: 2 | Journal Article |

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