Cited by 540Battery Modeling and ManagementElectric and Hybrid Vehicle TechnologiesAdvancements in Battery Materials

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Battery Management Systems in Electric and Hybrid Vehicles

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Xing, Yinjiao, Ma, Eden W. M., Tsui, Kwok L., Pecht, Michael·2011·Energies

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Abstract

The battery management system (BMS) is a critical component of electric and hybrid electric vehicles. The purpose of the BMS is to guarantee safe and reliable battery operation. To maintain the safety and reliability of the battery, state monitoring and evaluation, charge control, and cell balancing are functionalities that have been implemented in BMS. As an electrochemical product, a battery acts differently under different operational and environmental conditions. The uncertainty of a battery’s performance poses a challenge to the implementation of these functions. This paper addresses concerns for current BMSs. State evaluation of a battery, including state of charge, state of health, and state of life, is a critical task for a BMS. Through reviewing the latest methodologies for the state evaluation of batteries, the future challenges for BMSs are presented and possible solutions are proposed as well.

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BackgroundSelf-citation
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BackgroundMethod
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BackgroundMethodInfluential

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BackgroundMethod
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Background
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Estimation of State-of-charge and Sensor Fault Detection of a Lithium-ion Battery in Electric Vehicles
Han, M.-Y., & Lee, K.-S. (2014) · The Transactions of The Korean Institute of Electrical Engineers · doi:10.5370/kiee.2014.63.8.1085 · Cited by 3
“이 결과는 측정정보에 근거하여 구동되는 모델기반 SOC 추정 기법의 공통적인 문제로 판단되며, BMS의 신뢰성 확보를 위해 측정장치 오동작 및 고장을 조기에 검출, 식별해야함을 의미한다.”
Influential
Comparison of Nonlinear Filtering Methods for Estimating the State of Charge of Li4Ti5O12Lithium-Ion Battery
Gao, J., & He, H. (2015) · Mathematical Problems in Engineering · doi:10.1155/2015/485216 · Cited by 3
Online State of Charge Prediction in Next Generation Vehicle Batteries Using Deep Recurrent Neural Networks and Continuous Model Size Control
Hespeler, S. C., & Fuqua, D. (2021) · Journal of Energy and Power Technology · doi:10.21926/jept.2101003 · Cited by 3
State of Health Estimation of LiFePO4Battery based on Probability Density Function
Hou, C., Chen, J., Yang, S., & Chen, J. (2020) · IEEE Sustainable Power and Energy Conference (iSPEC) · doi:10.1109/ispec50848.2020.9351214 · Cited by 3
Environmental testing for reliable battery management system in electric vehicle
Raharjo, J., Wikarta, A., Sidharta, I., Yuniarto, M. N., Firdaus, M. I., & Zulhaimi, M. F. B. (2020) · Journal of Physics Conference Series · doi:10.1088/1742-6596/1517/1/012025 · Cited by 3
“BMS function is monitoring the battery condition from the battery voltage of each cell or State of Health (SOH), State of Charge (SOC), temperature, delta cell voltage, average voltage, and charging settings [4]–[7].”
Background
A high precision voltage reference circuit for battery management system chip of new energy electric vehicle
Ragchaa, B., He, X., Wu, L., & Zhang, X. (2022) · IEEE International Conference on Solid-State and Integrated Circuit Technology · doi:10.1109/icsict55466.2022.9963270 · Cited by 3
“Based on that information, the Battery Management Unit (BMU) of the electric car estimates the battery status, which prevents the power batteries from working beyond the safe operating area and keeps the balance of hundreds of series of battery cells in a battery-powered electric car [1][2].”
IoT Based Health Supervision of Energy Storage System
Ellahi, M., Khan, M. N., Hassan, M. W., Usman, H. F., Raza, A., & Khan, W. A. (2022) · International Conference on Electrical Engineering and Sustainable Technologies (ICEEST) · doi:10.1109/iceest56292.2022.10077875 · Cited by 3
Battery Capacity Trajectory Prediction with Multi-output Gaussian Process
Li, J., Deng, Z., & Hu, X. (2022) · International Conference on Smart Power & Internet Energy Systems (SPIES) · doi:10.1109/spies55999.2022.10082007 · Cited by 3
“However, lithium-ion batteries, a key energy source in a variety of systems, can often lead to a number of fatal errors as they age [5].”
Background
Alternatives in Battery Communication Protocols
Hong, H. J., Sevillano, J. R., Kain, C., Hofer, G., Felber, K., & Chan, W. K. (2017) · SAE technical papers on CD-ROM/SAE technical paper series · doi:10.4271/2017-01-1212 · Cited by 3
Development of a Lithium-ion Battery Model and State of Charge Estimation Algorithm with Hardware-in-the-loop Validation
Martínez-Vera, E., Marco, J., Ramírez-Cortés, J. M., & Rangel‐Magdaleno, J. (2019) · IEEE International Instrumentation and Measurement Technology Conference · doi:10.1109/i2mtc.2019.8827050 · Cited by 3
“Battery Management Systems (BMS) include the hardware and software required to monitor the status of the cells avoiding conditions of under/overcharging during operation of the batteries [5], [6].”
Method
A Multivariate Regression Method for Battery Remaining Capacity Based on Model Parameter Identification
Li, Y., Zhu, H., Zheng, J., & Chen, Y. (2021) · International Academic Exchange Conference on Science and Technology Innovation (IAECST) · doi:10.1109/iaecst54258.2021.9695670 · Cited by 3
The Effects of Driver Speed Prediction-Based Battery Management System on Li-ion Battery Performance for Electric Vehicles
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Control-oriented modeling and adaptive parameter estimation of a Lithium ion intercalation cell
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Modeling and Control of a Charge/Discharge Unit of Electric Power System for Low Earth Orbit Satellites
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Multilayer Neural Network-Based Battery Module SOH Diagnosis
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“According to Yinjiao Xing's paper, a battery should be replaced when its capacity is reduced to 80% of its rated beginning of life capacity [15].”
Review of Battery Management Strategy in Hybrid Lead-Acid-Lithium-Ion Energy Storage System for Transport Vehicles
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State of energy (SOE) estimation of LiNiCoAlO2 battery module considering cells unbalance and energy efficiency
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“Usually BMS estimates the state of charge (SOC) value of the battery that indicates the remaining charge that can be used from the battery [1].”
Background
PV - Battery Energy Storage Progress in Brazil: A ReviewPreprint
Mariano, J. D., de Freitas, P. M. B., de Medeiros, L., Block, P. A. B., Riboldi, V. B., Ji, T., & Urbanetz, J. (2021) · Preprints.org · doi:10.20944/preprints202105.0507.v1 · Cited by 3
“Regarding its operation, this device is more complex than the grid-tie PV inverter controlling the entire system including load controllers and their connection to the power grid [41, 42].”
Background
State of charge estimation of LiFePO4 batteries based on a transferable force-electric dual-observation model
Chang, C., Qu, B., Yu, H., Gao, Y., Liao, L., Lv, L., Wu, T., & Jiang, J. (2025) · Energy · doi:10.1016/j.energy.2025.137002 · Cited by 2
Multi-objective reinforcement learning for electric vehicle charging
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SOC and SOH Monitoring Algorithms for Lithium Batteries Using Multilayer Neural Networks
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Background
Remote Monitoring and Control of Battery Management System using CAN Communication and IoT Device for Cloud Based Analysis and Management
Earthineni, N., & Rao, V. S. (2023) · IEEE Conference on Information and Communication Technology (CICT) · doi:10.1109/cict59886.2023.10455594 · Cited by 2
NANOHEXCOOL: Advanced Thermal Control for Lithium-Ion Batteries
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In-situ powerline communication within lithium traction battery cells – Analysis of channel in various configurations
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Rancang Bangun Battery Monitoring System (BMS) berbasis LabVIEW
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Background
A Novel Battery Impedance Model Considering Internal Temperature Gradient
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Authors: Xing, Y., Ma, E. W. M., Tsui, K. L., & Pecht, M.
Affiliations: City University of Hong Kong (HK)
Corresponding author: Pecht, Michael
ORCID: Xing, Yinjiao
Tsui, Kwok L.
Pecht, Michael
Venue: Energies
Publisher: MDPI AG
Published: 2011-10-31
Volume: 4
Issue: 11
Pages: 1840-1857
ISSN: 1996-1073 (ISSN-L)
DOI: 10.3390/en4111840
OpenAlex: W2095027161
Cited by: 540
References: 33
Citations by year: 2026: 35 · 2025: 48 · 2024: 50 · 2023: 53 · 2022: 43 · 2021: 63 · 2020: 37 · 2019: 43 · 2018: 31 · 2017: 37 · 2016: 27 · 2015: 26 · 2014: 24 · 2013: 18 · 2012: 5
FWCI: 30.79
Type: journal article
Language: en
Open access: gold
doi.org
Licence: cc-by
creativecommons.org/licenses/by/3.0/ (vor)
Locations: Energies (publishedVersion, cc-by)
RePEc: Research Papers in Economics (submittedVersion)
DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
CityU Scholars (submittedVersion, cc-by)
Funders: City University of Hong Kong
Topics: Physical Sciences › Engineering › Automotive Engineering › Battery Modeling and Management
Physical Sciences › Engineering › Automotive Engineering › Electric and Hybrid Vehicle Technologies
Physical Sciences › Engineering › Electrical and Electronic Engineering › Advancements in Battery Materials
Keywords: battery management systems, electric vehicles, hybrid electric vehicles, state of charge estimation, state of health estimation, battery state monitoring, charge control, battery balancing

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Battery Management Systems in Electric and Hybrid Vehicles

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