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Battery Insulation Performance Analysis in Electric Vehicles for the Improvement of Battery Lifetime

Lora Khaula Amifia, Nuansa Dipa Bismoko, Philip Tobianto Daely

Abstract


The battery is the main component both as an energy provider and as an interface for several systems in an electric vehicle. It has three important parameters: current, voltage, and temperature that must be maintained as the battery can have a harmful reaction that can lead to overcurrent. The battery must also not overcharging or discharging for too long because it can cause damage and affect its lifetime. Another error that can arise is sensor failure due to the interference or noise that can cause an error in data reading. To prevent this problem, it needs protection by means of isolation in operating the battery. In this research, planning in optimizing battery work was conducted by designing the process of detection and isolation of faults that occurred in batteries, particularly lithium polymer battery to reach their more optimal and good performance. Battery modeling was needed as the parameter identification, and the Kalman Filter algorithm was applied to help to reduce the detection rate and fault isolation. The results of detection and isolation of overcurrent and sensor failure using Kalman Filter were found quite accurate. In overcurrent isolation, a discharge current of 6A was obtained from the maximum current limit of 10 A, and for sensor failure isolation, the Kalman Filter algorithm succeeded in improving the results of the previous reading.

Keywords


Lithium Polymer Battery; Fault Detection; Fault Isolation; Battery Modelling.

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References


M. Kim, K. Kim, and S. Han, “Reliable Online Parameter Identification of Li-Ion Batteries in Battery Management Systems Using the Condition Number of the Error Covariance Matrix,†IEEE Access, vol. 8, pp. 189106–189114, 2020. https://doi.org/10.1109/ACCESS.2020.3031500

Q. Wei, D. Liu, Y. Liu, and R. Song, “Optimal constrained self-learning battery sequential management in microgrid via adaptive dynamic programming,†IEEE/CAA J. Autom. Sin., vol. 4, no. 2, pp. 168–176, 2017. https://doi.org/10.1109/JAS.2016.7510262

S. Zeinal-Kheiri, A. M. Shotorbani, and B. Mohammadi-Ivatloo, “Real-time Energy Management of Grid-connected Microgrid with Flexible and Delay-tolerant Loads,†J. Mod. Power Syst. Clean Energy, vol. 8, no. 6, pp. 1196–1207, 2020. https://doi.org/10.35833/MPCE.2018.000615

Q. Zhang, W. Deng, and G. Li, “Stochastic Control of Predictive Power Management for Battery/Supercapacitor Hybrid Energy Storage Systems of Electric Vehicles,†IEEE Trans. Ind. Informatics, vol. 14, no. 7, pp. 3023–3030, 2018. https://doi.org/10.1109/TII.2017.2766095

Z. Sun, P. Liu, and Z. Wang, “Real-time fault diagnosis method of battery system based on Shannon entropy,†Energy Procedia, vol. 105, pp. 2354–2359, 2017. https://doi.org/10.1016/j.egypro.2017.03.676

N. Ullah, Z. Farooq, I. Sami, M. S. Chowdhury, K. Techato, and H. Alkhammash, “Industrial Grade Adaptive Control Scheme for a Micro-Grid Integrated Dual Active Bridge Driven Battery Storage System,†IEEE Access, vol. 8, pp. 210435–210451, 2020. https://doi.org/10.1109/ACCESS.2020.3039947

Y. Pan, X. Feng, M. Zhang, X. Han, L. Lu, and M. Ouyang, “Internal short circuit detection for lithium-ion battery pack with parallel-series hybrid connections,†J. Clean. Prod., vol. 255, p. 120277, 2020. https://doi.org/10.1016/j.jclepro.2020.120277

X. Kong, Y. Zheng, M. Ouyang, L. Lu, and J. Li, “Fault diagnosis and quantitative analysis of micro-short circuits for lithium-ion batteries in battery packs,†J. Power Sources, vol. 395, pp. 358–368, 2018. https://doi.org/10.1016/j.jpowsour.2018.05.097

X. Lai, W. Yi, X. Kong, X. Han, L. Zhou, T. Sun, and Y. Zheng, “Online detection of early stage internal short circuits in series-connected lithium-ion battery packs based on state-of-charge correlation,†Journal of Energy Storage, vol. 30, p. 101514, Aug. 2020. https://doi.org/10.1016/j.est.2020.101514

J. Jiang, X. Cong, S. Li, C. Zhang, W. Zhang, and Y. Jiang, “A Hybrid Signal-Based Fault Diagnosis Method for Lithium-Ion Batteries in Electric Vehicles,†IEEE Access, vol. 9, pp. 19175–19186, 2021. https://doi.org/10.1109/ACCESS.2021.3052866

N. Yadav and N. R. Tummuru, “Fault Detection and Isolation Technique in Low Voltage DC Microgrid Based on Terminal Resistance of DC Circuit Breakers,†2020 IEEE International Conference on Power Electronics, Smart Grid and Renewable Energy (PESGRE2020), Jan. 2020. https://doi.org/10.1109/PESGRE45664.2020.9070425

S. M. M. Alavi, S. Fekriasl, S. N. Niyakan, and M. Saif, “Fault detection and isolation in batteries power electronics and chargers,†Journal of Energy Storage, vol. 25, p. 100807, Oct. 2019. https://doi.org/10.1016/j.est.2019.100807

S. Dey, H. E. Perez, and S. J. Moura, “Robust fault detection of a class of uncertain linear parabolic PDEs,†Automatica, vol. 107, pp. 502–510, Sep. 2019. https://doi.org/10.1016/j.automatica.2019.06.014

R. Xiong, W. Sun, Q. Yu, and F. Sun, “Research progress, challenges and prospects of fault diagnosis on battery system of electric vehicles,†Appl. Energy, vol. 279, no. 2, p. 115855, 2020. https://doi.org/10.1016/j.apenergy.2020.115855

J. Zhang, “A Model-Based Method for Fault Detection and Isolation of Electric Drive Systems,†2020 IEEE International Conference on Prognostics and Health Management (ICPHM), 2020. https://doi.org/10.1109/ICPHM49022.2020.9187028

Y. Kang, B. Duan, Z. Zhou, Y. Shang, and C. Zhang, “A multi-fault diagnostic method based on an interleaved voltage measurement topology for series connected battery packs,†J. Power Sources, vol. 417, pp. 132–144, 2019. https://doi.org/10.1016/j.jpowsour.2019.01.058

L. Yao, Z. Fang, Y. Xiao, J. Hou, and Z. Fu, “An Intelligent Fault Diagnosis Method for Lithium Battery Systems Based on Grid Search Support Vector Machine,†Energy, vol. 214, p. 118866, Jan. 2021. https://doi.org/10.1016/j.energy.2020.118866

H. Aung, J. J. Soon, S. T. Goh, J. M. Lew, and K. S. Low, “Battery Management System with State-of-Charge and Opportunistic State-of-Health for a Miniaturized Satellite,†IEEE Trans. Aerosp. Electron. Syst., vol. 56, no. 4, pp. 2978–2989, 2020. https://doi.org/10.1109/TAES.2019.2958161

C. Zheng, Z. Chen, and D. Huang, “Fault diagnosis of voltage sensor and current sensor for lithium-ion battery pack using hybrid system modeling and unscented particle filter,†Energy, vol. 191, p. 116504, Jan. 2020. https://doi.org/10.1016/j.energy.2019.116504

Y. C. H. Yuwono, B. R. Dewangga, A. I. Cahyadi, and S. Herdjunanto, “Fault Detection on The Battery SOC-OCV by Using Observer,†2018 4th Int. Conf. Sci. Technol., pp. 1–4, 2018. https://doi.org/10.1109/ICSTC.2018.8528607

A. Dhoke, R. Sharma, and T. K. Saha, “A technique for fault detection, identification and location in solar photovoltaic systems,†Sol. Energy, vol. 206, pp. 864–874, 2020. https://doi.org/10.1016/j.solener.2020.06.019

J. Meng, M. Boukhnifer, and D. Diallo, “On-line Model-based Short Circuit Diagnosis of Lithium-Ion Batteries for Electric Vehicle Application,†IECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society, 2019, pp. 6022-6027. https://doi.org/10.1109/IECON.2019.8927671

A. Naha, A. Khandelwal, K. S. Hariharan, A. Kaushik, A. Yadu, and S. M. Kolake, “On-Board Short-Circuit Detection of Li-ion Batteries Undergoing Fixed Charging Profile as in Smartphone Applications,†IEEE Transactions on Industrial Electronics, vol. 66, no. 11, pp. 8782–8791, Nov. 2019. https://doi.org/10.1109/TIE.2018.2889623

Q. Xue, G. Li, Y. Zhang, S. Shen, Z. Chen, and Y. Liu, “Fault diagnosis and abnormality detection of lithium-ion battery packs based on statistical distribution,†Journal of Power Sources, vol. 482, p. 228964, Jan. 2021. https://doi.org/10.1016/j.jpowsour.2020.228964

R. Xiong, Q. Yu, W. Shen, C. Lin, and F. Sun, “A Sensor Fault Diagnosis Method for a Lithium-Ion Battery Pack in Electric Vehicles,†IEEE Transactions on Power Electronics, vol. 34, no. 10, pp. 9709–9718, Oct. 2019. https://doi.org/10.1109/TPEL.2019.2893622

W. Gao, X. Li, M. Ma, Y. Fu, J. Jiang, and C. Mi, “Case Study of an Electric Vehicle Battery Thermal Runaway and Online Internal Short-Circuit Detection,†IEEE Transactions on Power Electronics, vol. 36, no. 3, pp. 2452–2455, Mar. 2021. https://doi.org/10.1109/TPEL.2020.3013191

X. Fan, W. Zhang, Z. Wang, F. An, H. Li, and J. Jiang, “Simplified Battery Pack Modeling Considering Inconsistency and Evolution of Current Distribution,†IEEE Trans. Intell. Transp. Syst., vol. 22, no. 1, pp. 630–639, 2021. https://doi.org/10.1109/TITS.2020.3010567

H. Rozas, R. M. Claveria, M. E. Orchard, and K. Medjaher, “Residual-based scheme for detection and characterization of faults in lithium-ion batteries,†IFAC-PapersOnLine, vol. 51, no. 24, pp. 200–207, 2018. https://doi.org/10.1016/j.ifacol.2018.09.578

Z. Chen, K. Xu, J. Wei, and G. Dong, “Voltage fault detection for lithium-ion battery pack using local outlier factor,†Measurement, vol. 146, pp. 544–556, Nov. 2019. https://doi.org/10.1016/j.measurement.2019.06.052

R. Yang, R. Xiong, H. He, and Z. Chen, “A fractional-order model-based battery external short circuit fault diagnosis approach for all-climate electric vehicles application,†Journal of Cleaner Production, vol. 187, pp. 950–959, Jun. 2018. https://doi.org/10.1016/j.jclepro.2018.03.259

Z. Song, F. P. Delgado, J. Hou, H. Hofmann, and J. Sun, “Individual Cell Fault Detection for Parallel-Connected Battery Cells Based on the Statistical Model and Analysis,†2020 American Control Conference (ACC), 2020, pp. 1155-1160. https://doi.org/10.23919/ACC45564.2020.9147423

Z. B. Omariba, L. Zhang, and D. Sun, “Review of Battery Cell Balancing Methodologies for Optimizing Battery Pack Performance in Electric Vehicles,†IEEE Access, vol. 7, pp. 129335–129352, 2019. https://doi.org/10.1109/ACCESS.2019.2940090




DOI: http://dx.doi.org/10.26555/jiteki.v7i3.22199

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Jurnal Ilmiah Teknik Elektro Komputer dan Informatika
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Organized by Electrical Engineering Department - Universitas Ahmad Dahlan
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