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Accurate forecasting of battery health indicators, including remaining capacity and lifetime, is of paramount importance for ensuring the reliability, safety, and operational efficiency of applications such as electric vehicles and large…

Signal Processing · Electrical Eng. & Systems 2026-05-29 Athanasios Koukosias , Vasileios Tzanidakis , Sotiris Athanasiou , Kostas Kolomvatsos

Degradation prediction for lithium-ion batteries using data-driven methods requires high-quality aging data. However, generating such data, whether in the laboratory or the field, is time- and resource-intensive. Here, we propose a method…

Systems and Control · Electrical Eng. & Systems 2025-03-19 Weihan Li , Harshvardhan Samsukha , Bruis van Vlijmen , Lisen Yan , Samuel Greenbank , Simona Onori , Venkat Viswanathan

Advancing lithium-ion batteries (LIBs) in both design and usage is key to promoting electrification in the coming decades to mitigate human-caused climate change. Inadequate understanding of LIB degradation is an important bottleneck that…

Machine Learning · Computer Science 2024-04-04 Jing Lin , Yu Zhang , Edwin Khoo

The usability of vehicles is highly dependent on their energy consumption. In particular, one of the main factors hindering the mass adoption of electric (EV), hybrid (HEV), and plug-in hybrid (PHEV) vehicles is range anxiety, which occurs…

Machine Learning · Computer Science 2023-04-18 Jihed Khiari , Cristina Olaverri-Monreal

As the number of electric vehicles rapidly increases, their peak demand on the grid becomes one of the major challenges. A battery-assisted charging concept has emerged recently, which allows to accumulate energy during off-peak hours and…

Systems and Control · Electrical Eng. & Systems 2020-11-16 Junade Ali , Vladimir Dyo , Sijing Zhang

Health evaluation for lithium-ion batteries (LIBs) typically relies on constant charging/discharging protocols, often neglecting scenarios involving dynamic current profiles prevalent in electric vehicles. Conventional health indicators for…

Machine Learning · Computer Science 2025-03-12 J. C. Chen

Widespread electric vehicle (EV) adoption introduces new challenges for distribution grids due to large, localized load increases, stochastic charging behavior, and limited data availability. This paper proposes two data-driven methods to…

Systems and Control · Electrical Eng. & Systems 2025-11-19 Linhan Fang , Jesus Silva-Rodriguez , Xingpeng Li

Dynamic models of the battery performance are an essential tool throughout the development process of automotive drive trains. The present study introduces a method making a large data set suitable for modeling the electrical impedance.…

Machine Learning · Computer Science 2020-12-08 Philipp Gesner , Christian Gletter , Florian Landenberger , Frank Kirschbaum , Lutz Morawietz , Bernard Bäker

The rapid expansion of electric vehicles has intensified the need for accurate and efficient diagnosis of lithium-ion batteries. Parameter identification of electrochemical battery models is widely recognized as a powerful method for…

Machine Learning · Computer Science 2025-10-29 Hojin Cheon , Hyeongseok Seo , Jihun Jeon , Wooju Lee , Dohyun Jeong , Hongseok Kim

The adoption of electric vehicles (EVs) is rapidly growing as a key solution to reducing greenhouse gas emissions. However, prolonged charging times remain a significant barrier to widespread EV usage, especially for individuals without…

Systems and Control · Electrical Eng. & Systems 2025-07-17 Jonathan Olivares , Tyler Depe , Rakeshkumar Mahto

This paper presents a combination of machine learning techniques to enable prompt evaluation of retired electric vehicle batteries as to either retain those batteries for a second-life application and extend their operation beyond the…

Systems and Control · Electrical Eng. & Systems 2023-04-10 Aki Takahashi , Anirudh Allam , Simona Onori

Batteries are a key enabling technology for the decarbonization of transport and energy sectors. The safe and reliable operation of batteries is crucial for battery-powered systems. In this direction, the development of accurate and robust…

Machine Learning · Computer Science 2024-07-16 Jokin Alcibar , Jose I. Aizpurua , Ekhi Zugasti

Lithium-ion batteries are pivotal to technological advancements in transportation, electronics, and clean energy storage. The optimal operation and safety of these batteries require proper and reliable estimation of battery capacities to…

Machine Learning · Computer Science 2024-07-24 Gift Modekwe , Saif Al-Wahaibi , Qiugang Lu

We propose a data-driven, user-centric vehicle-to-grid (V2G) methodology based on multi-objective optimization to balance battery degradation and V2G revenue according to EV user preference. Given the lack of accurate and generalizable…

Systems and Control · Electrical Eng. & Systems 2025-05-30 Arghya Mallick , Georgios Pantazis , Mohammad Khosravi , Peyman Mohajerin Esfahani , Sergio Grammatico

Electric Vehicle (EV) fast charging stations require forecasting techniques both at the single charger level and aggregated level. While for the latter several models exist, forecasting individual EV charging profiles is still underexplored…

Systems and Control · Electrical Eng. & Systems 2026-05-19 Riccardo Ramaschi , Mario Paolone , Sonia Leva

- This work has been submitted to IFAC for possible publication - Models of traction batteries are an essential tool throughout the development of automotive drivetrains. Surprisingly, today's massively collected battery data is not yet…

Machine Learning · Computer Science 2021-01-01 Philipp Gesner , Frank Kirschbaum , Richard Jakobi , Bernard Bäker

Accurate battery capacity estimation is key to alleviating consumer concerns about battery performance and reliability of electric vehicles (EVs). However, practical data limitations imposed by stringent privacy regulations and labeled data…

Machine Learning · Computer Science 2025-10-20 Anushiya Arunan , Yan Qin , Xiaoli Li , U-Xuan Tan , H. Vincent Poor , Chau Yuen

The degradation process of lithium-ion batteries is intricately linked to their entire lifecycle as power sources and energy storage devices, encompassing aspects such as performance delivery and cycling utilization. Consequently, the…

Machine Learning · Computer Science 2023-08-16 Yue Xiang , Bo Jiang , Haifeng Dai

Accurate estimation of battery state of health is crucial for effective electric vehicle battery management. Here, we propose five health indicators that can be extracted online from real-world electric vehicle operation and develop a…

Machine Learning · Computer Science 2024-09-24 Andrea Lanubile , Pietro Bosoni , Gabriele Pozzato , Anirudh Allam , Matteo Acquarone , Simona Onori

Carbon emissions are rising at an alarming rate, posing a significant threat to global efforts to mitigate climate change. Electric vehicles have emerged as a promising solution, but their reliance on lithium-ion batteries introduces the…

Machine Learning · Computer Science 2024-10-21 Sharv Murgai , Hrishikesh Bhagwat , Raj Abhijit Dandekar , Rajat Dandekar , Sreedath Panat