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Battery Management Systems in Electric and Hybrid Vehicles
Open accessAbstract
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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“Other authors, such as Xing et al. [88], present a review of BMS for Battery Electric (BEVs) and Hybrid Vehicles (HVs) when considering the state of charge, the state of health, and the state of life, as the key features to be considered by BMSs.”
From A Review on Electric Vehicles: Technologies and Challenges (2021) · cites this paper as [88]
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Citations
Cites
Lithium Batteries: Status, Prospects and Future
Scrosati, B., & Garche, J. (2010) · Journal of Power Sources · doi:10.1016/j.jpowsour.2009.11.048 · Cited by 5,153 · cited 1×
“From the perspective of chemical characteristics, Scrosati and Garche [13] presented voltage-to-capacity profiles of several Li/Li+ materials.”
BackgroundExtended Kalman filtering for battery management systems of LiPB-based HEV battery packs
Plett, G. L. (2004) · Journal of Power Sources · doi:10.1016/j.jpowsour.2004.02.033 · Cited by 1,768
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“The ratio of the currently available capacity to the maximum capacity can be expressed as SOC [25], which is calculated by Equation (1):”
BackgroundA Generic Battery Model for the Dynamic Simulation of Hybrid Electric Vehicles
Tremblay, O., Dessaint, L., & Dekkiche, A. (2007) · IEEE Vehicle Power and Propulsion Conference (VPPC) · doi:10.1109/vppc.2007.4544139 · Cited by 1,309 · cited 1×
“Cheng [17] and Tremblay [18] adopted the generic battery model that was integrated in MATLAB [19].”
MethodBattery thermal models for hybrid vehicle simulations
Pesaran, A. A. (2002) · Journal of Power Sources · doi:10.1016/s0378-7753(02)00200-8 · Cited by 1,116 · cited 1×
“Thus, Pesaran [39] pointed out that it is important to reduce the temperature difference among cells, which must be monitored and operated under proper temperature conditions.”
BackgroundHe, W., Williard, N., Osterman, M., & Pecht, M. (2011) · Journal of Power Sources · doi:10.1016/j.jpowsour.2011.08.040 · Cited by 1,105 · cited 1×
“He [37] developed a degradation model for lithium-ion batteries according to a new exponential model.”
BackgroundSelf-citationTipping, M. E. (1999) · Cited by 869
Prognostics methods for battery health monitoring using a bayesian framework
Saha, B., Goebel, K., Poll, S., & Christophersen, J. (2009) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2008.2005965 · Cited by 831 · cited 1×
“Saha [36] also used an RVM regression model, which was built using internal battery parameters from EIS data.”
MethodA review on prognostics and health monitoring of Li-ion battery
Zhang, J., & Lee, J. (2011) · Journal of Power Sources · doi:10.1016/j.jpowsour.2011.03.101 · Cited by 792 · cited 3×
“Determination of SOC and SOH will be integrated into a capability assessment, which also presents the life status of the battery and sets the operating limits according to state-of-the-art algorithms, such as fuzzy logic, neural networks, state-space-based models, and so on [17,27,29].”
BackgroundMethodBattery-Management System (BMS) and SOC Development for Electrical Vehicles
Cheng, K. W. E., Divakar, B. P., Wu, H., Ding, K., & Ho, H. F. J. (2010) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2010.2089647 · Cited by 696 · cited 5×
“Cheng [17] and Tremblay [18] adopted the generic battery model that was integrated in MATLAB [19].”
BackgroundMethodInfluentialBattery balancing methods: A comprehensive review
Cao, J. B., Schofield, N., & Emadi, A. (2008) · IEEE Vehicle Power and Propulsion Conference (VPPC) · doi:10.1109/vppc.2008.4677669 · Cited by 658 · cited 1×
“imbalance [23].”
Simulation of capacity fade in lithium-ion batteries
Spotnitz, R. M. (2002) · Journal of Power Sources · doi:10.1016/s0378-7753(02)00490-1 · Cited by 594 · cited 1×
“While taking into account SOH estimation, the battery degradation model based on capacity fade was simulated and built [20–22].”
MethodDetermination of state-of-charge and state-of-health of batteries by fuzzy logic methodology
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“[29] utilized Electrochemical Impedance Spectroscopy (EIS) data to estimate SOC with fuzzy logic.”
BackgroundMethodBattery Management Systems for Large Lithium Ion Battery Packs
Andrea, D. (2010) · Cited by 405
Intelligent prognostics for battery health monitoring based on sample entropy
Widodo, A., Shim, M.-C., Caesarendra, W., & Yang, B.-S. (2011) · Expert Systems with Applications · doi:10.1016/j.eswa.2011.03.063 · Cited by 392 · cited 3×
“Coup de Fouet voltage [35], internal resistance and transient current, were input into a modified extension matter-element model to develop intelligent SOH evaluation [32].”
BackgroundMethodSupport vector based battery state of charge estimator
Hansen, T., & Wang, C.-J. (2005) · Journal of Power Sources · doi:10.1016/j.jpowsour.2004.09.020 · Cited by 347 · cited 1×
“Hansen and Wang [30] applied a support vector machine (SVM) using both classification and regression to estimate the SOC without establishing a battery circuit model.”
MethodCapacity fade analysis of a lithium ion cell
Zhang, Q., & White, R. E. (2008) · Journal of Power Sources · doi:10.1016/j.jpowsour.2008.01.028 · Cited by 290 · cited 1×
“While taking into account SOH estimation, the battery degradation model based on capacity fade was simulated and built [20–22].”
MethodBattery Monitoring and Electrical Energy Management
Meissner, E., & Richter, G. (2003) · Journal of Power Sources · doi:10.1016/s0378-7753(02)00713-9 · Cited by 257 · cited 1×
“Meissner and Richter [7] proposed a layer structure for battery monitoring, battery state, and battery management.”
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“Uno [24] studied the influence of high frequency on the life performance of lithium-ion cells.”
BackgroundMaterials and processing for lithium-ion batteries
Daniel, C. (2008) · JOM · doi:10.1007/s11837-008-0116-x · Cited by 192
A PSPICE macromodel for lithium-ion batteries
Gold, S. (2002) · doi:10.1109/bcaa.1997.574106 · Cited by 157 · cited 1×
“Gold [8] categorized the different functions in a BMS.”
BackgroundOptimized battery-management system to improve storage lifetime in renewable energy systems
Kaiser, R. (2006) · Journal of Power Sources · doi:10.1016/j.jpowsour.2006.12.024 · Cited by 151 · cited 1×
“A literature review has revealed that BMSs are still in a premature stage [40].”
BackgroundComprehensive dynamic battery modeling for PHEV applications
Zhang, H., & Chow, M. (2010) · IEEE Power Engineering Society General Meeting · doi:10.1109/pes.2010.5590108 · Cited by 148 · cited 1×
“Currently, battery modeling for SOC determination is commonly developed from various equivalent circuit (RC network) models, which are distinct for different material characteristics and accuracy requirements [14–16].”
Kozlowski, J. D. (2004) · IEEE Aerospace Conference (AERO) · doi:10.1109/aero.2003.1234169 · Cited by 136 · cited 5×
“Some researchers have proposed adopting EIS to monitor internal impedance [12,26].”
BackgroundMethodInfluentialAnalysis of capacity fade in a lithium ion battery
Stamps, A. T., Holland, C. E., White, R. E., & Gatzke, E. P. (2005) · Journal of Power Sources · doi:10.1016/j.jpowsour.2005.02.033 · Cited by 102 · cited 1×
“While taking into account SOH estimation, the battery degradation model based on capacity fade was simulated and built [20–22].”
MethodAutomotive battery management systems
Pattipati, B., Pattipati, K. R., Christopherson, J. P., Namburu, S. M., Prokhorov, D. V., & Qiao, L. (2008) · IEEE AUTOTESTCON (IEEE Systems Readiness Technology Conference) · doi:10.1109/autest.2008.4662684 · Cited by 101
A Modular Battery Management System for HEVs
Stuart, T. A., Fang, F., Wang, X., Ashtiani, C., & Pesaran, A. A. (2002) · SAE technical papers on CD-ROM/SAE technical paper series · doi:10.4271/2002-01-1918 · Cited by 73
Reliable battery operation — a challenge for the battery management system
Jossen, A., Späth, V., Döring, H., & Garche, J. (1999) · Journal of Power Sources · doi:10.1016/s0378-7753(99)00329-8 · Cited by 69 · cited 1×
“Communication through a CAN Bus is a major way to transfer data within the BMS [17,38].”
Windarko, N. A., Choi, J., & Chung, G.-B. (2011) · doi:10.1109/icpe.2011.5944483 · Cited by 38 · cited 1×
“Windarko [14] also adopted the EKF to estimate SOC based on an electrical model with two series RC networks.”
MethodChao, K., & Chen, J. (2011) · Expert Systems with Applications · doi:10.1016/j.eswa.2011.05.084 · Cited by 27 · cited 2×
“Cheng [17] and Tremblay [18] adopted the generic battery model that was integrated in MATLAB [19].”
BackgroundStandby Power System VRLA Battery Reserve Life Estimation Scheme
Pascoe, P. E., & Al‐Anbuky, A. (2005) · IEEE Transactions on Energy Conversion · doi:10.1109/tec.2005.853749 · Cited by 27 · cited 1×
“Coup de Fouet voltage [35], internal resistance and transient current, were input into a modified extension matter-element model to develop intelligent SOH evaluation [32].”
MethodBattery state-of-charge estimation based on H∞ filter for hybrid electric vehicle
Yan, J., Xu, G., Xu, Y., & Xie, B. (2008) · International Conference on Control, Automation, Robotics and Vision (ICARCV) · doi:10.1109/icarcv.2008.4795563 · Cited by 16
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Hannan, M. A., Lipu, M. S. H., Hussain, A., & Mohamed, A. (2017) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2017.05.001 · Cited by 2,005
A Review on Electric Vehicles: Technologies and Challenges
Sanguesa, J. A., Torres-Sanz, V., Garrido, P., Martinez, F. J., & Marquez-Barja, J. M. (2021) · Smart Cities · doi:10.3390/smartcities4010022 · Cited by 1,367
“[88], present a review of BMS for Battery Electric (BEVs) and Hybrid Vehicles (HVs) when considering the state of charge, the state of health, and the state of life, as the key features to be considered by BMSs.”
A critical review of battery thermal performance and liquid based battery thermal management
Wu, W., Wang, S., Wu, W. T., Chen, K., Hong, S., & Lai, Y. (2019) · Energy Conversion and Management · doi:10.1016/j.enconman.2018.12.051 · Cited by 1,243
Review of energy storage systems for electric vehicle applications: Issues and challenges
Hannan, M. A., Hoque, M. M., Mohamed, A., & Ayob, A. (2016) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2016.11.171 · Cited by 1,067
Critical Review on the Battery State of Charge Estimation Methods for Electric Vehicles
Xiong, R., Cao, J., Yu, Q., He, H., & Sun, F. (2017) · IEEE Access · doi:10.1109/access.2017.2780258 · Cited by 1,046
Metadata
- Authors
- Xing, Y., Ma, E. W. M., Tsui, K. L., & Pecht, M.
- Affiliations
- City University of Hong Kong (HK)
- Corresponding author
- Pecht, Michael
- Venue
- Energies
- Publisher
- MDPI AG
- Published
- 2011-10-31
- Volume
- 4
- Issue
- 11
- Pages
- 1840-1857
- ISSN
- 1996-1073 (ISSN-L)
- 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
- 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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