Article
Energy & Fuels
Tae -Won Noh, Dong Hwan Kim, Byoung Kuk Lee
Summary: In this study, a novel online state-of-health (SOH) estimation algorithm for electric vehicles (EVs) is proposed based on the compression ratio of open circuit voltage (OCV)-to-charged capacity curve. The proposed algorithm estimates the degraded capacity at every sampling time during the driving operation through a first-order low-pass filter, which does not require complex mathematical tools and numerous offline data.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Thermodynamics
Xiong Feng, Junxiong Chen, Zhongwei Zhang, Shuwen Miao, Qiao Zhu
Summary: This paper presents a novel neural network structure called CWRNN, which effectively addresses long-term dependencies, reduces training and computation costs, and is validated under different temperature conditions.
Article
Energy & Fuels
Lin Wang, Xiaowei Zhao, Zhongwei Deng, Lin Yang
Summary: This paper focuses on the accurate estimation of State of Charge (SoC) for electric vehicles and hybrid electric vehicles. A new model updating strategy based on electrochemical impedance spectroscopy (EIS) is proposed, which effectively enhances the SoC estimation accuracy by modifying model parameters and capacity according to the change rate of ohmic impedance.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Energy & Fuels
Shuangqi Li, Hongwen He, Pengfei Zhao, Shuang Cheng
Summary: This paper proposes a method for battery modeling using deep transfer learning and multi-source data, and the experimental results show that the error of the battery model can be limited to 2.43% and 1.27% throughout the entire lifecycle.
Article
Thermodynamics
Chunsheng Hu, Liang Ma, Shanshan Guo, Gangsheng Guo, Zhiqiang Han
Summary: This paper proposes a method for estimating the state of charge (SoC) of LiFePO4 batteries during the charging process using a deep neural network (DNN). Battery data collected from different charging protocols are used to train the DNN model. The developed DNN can accurately estimate the battery's SoC during charging and can be used to calculate the SoC during discharging. Experimental results show that the maximum error and root mean square error of the SoC estimation using DNN are within an acceptable range.
Article
Engineering, Electrical & Electronic
Ning Li, Fuxing He, Wentao Ma, Ruotong Wang, Lin Jiang, Xiaoping Zhang
Summary: This article proposes an indirect SOH estimation method for online EV lithium-ion batteries based on arctangent function adaptive genetic algorithm combination with back propagation neural network (ATAGA-BP). The simulation results with NASA data show that the proposed method has high correlation and low estimation error.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2022)
Article
Thermodynamics
Yousif M. Alkhulaifi, Naef A. A. Qasem, Syed M. Zubair
Summary: This paper compares the performance of an ejector-based battery thermal management system (BTMS) to a basic system from thermal and exergoeconomic perspectives. The results show that the ejector-based system has a lower total cost rate and energy consumption, demonstrating its technical and economic feasibility for thermal management in electric and hybrid electric vehicles.
Article
Energy & Fuels
Mouncef El Marghichi, Azeddine Loulijat, Soufiane Dangoury, Hamid Chojaa, Almoataz Y. Abdelaziz, Mahmoud A. Mossa, Junhee Hong, Zong Woo Geem
Summary: Accurate assessment of battery capacity is crucial for battery management systems. This research successfully improves the precision of battery capacity estimation by mitigating uncertainties in state of charge estimation and measurement using the bald eagle search algorithm. Experimental results demonstrate the superiority of this method, with a maximum error rate of only 1.06%.
Review
Computer Science, Information Systems
T. Girijaprasanna, C. Dhanamjayulu
Summary: This research explores the importance of Battery Management System (BMS) and accurate estimation of State of Charge (SOC) in electric vehicles (EVs). The article presents advanced SOC estimation techniques and provides a detailed comparison and evaluation. The study also identifies factors, challenges, and recommendations for improving BMS and estimating approaches for future sustainable EV applications.
Article
Energy & Fuels
Kaixuan Zhang, Cheng Chen, Yanzhou Duan, Yu Fang, Ruixin Yang
Summary: This paper proposes a new method to describe the relation between OCV and SOC, simplifying the mapping between temperature, aging, OCV, and SOC into a temperature-independent three-dimensional mapping. The newly-defined capacity and OCV-SOC curve are independent of battery temperature and have been verified with a large number of test data. A cooperative estimation method for model parameters and state based on the DEKF algorithm is developed, and the results show that the proposed method can accurately estimate battery SOC with an error within 3% after fast convergence.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Energy & Fuels
Zhicheng Xu, Chuang Zhang, Bo Sun, SuZhen Liu
Summary: The widespread deployment of electric vehicles not only relates to the electrification reform of the transport sector, but also plays a crucial role in the low-carbon transformation for urban energy systems. The performance, cost, and safety of electric vehicles are heavily influenced by the lithium-ion battery, which serves as the main energy supply. Strengthening the energy management of the lithium-ion battery system is essential to ensure its efficiency and safety. This study utilizes a prototype simulation system to estimate and predict the electrical and thermal properties of multi-level batteries and accurately assess the battery state, showing its capability in guaranteeing the safe and stable operation of the lithium-ion battery system.
JOURNAL OF ENERGY STORAGE
(2023)
Review
Chemistry, Physical
Mohammad Waseem, Mumtaz Ahmad, Aasiya Parveen, Mohd Suhaib
Summary: This article summarizes the current state, energy storage options, charging techniques, challenges, and future prospects of electric vehicles (EVs) and their batteries and battery management systems (BMS). The importance of research and development towards EVs lies in their eco-friendly nature, suppression of petroleum products, greener transport, and zero carbon emissions.
JOURNAL OF POWER SOURCES
(2023)
Article
Energy & Fuels
El Marghichi Mouncef, Bouzi Mostafa
Summary: This paper proposes a battery capacity estimation framework based on the sunflower optimization algorithm, which takes into account capacity error sources and uses a reduction strategy of the search space to enhance accuracy. Experimental results demonstrate that this approach has high accuracy and predictive performance.
JOURNAL OF ENERGY STORAGE
(2022)
Article
Thermodynamics
A. Maheshwari, S. Nageswari
Summary: This paper focuses on the estimation of the battery's State of Charge (SOC) in a battery management system, proposing an optimization algorithm based on EKF and SFO to improve estimation accuracy and convergence speed.
Review
Chemistry, Physical
Alessandro M. Ralls, Kaitlin Leong, Jennifer Clayton, Phillip Fuelling, Cody Mercer, Vincent Navarro, Pradeep L. Menezes
Summary: Within the automotive field, there has been an increasing focus on the usability of combustion-independent electric vehicles (EVs). This is due to the popularity and practicality of EVs powered by Li-ion batteries (LIBs). However, there hasn't been a comprehensive review covering the current advancements of LIBs from economic, industrial, and technical perspectives. This literature review suggests that there is still room for overall advancement in EV-based LIBs, making it a hot topic for the coming years.
