Charge and Health Status Estimation of a Lithium Ion Battery in an Electric Vehicle using Cell Balancing IOT Modeling Techniques

Rakshitha Ravi

Battery Management System; Open Circuit Voltage; Kalman Filter; State of Charge.

In Present scenario Internal Combustion Engines [ICE] is overcome by Electric Vehicles [EV] due to advantages like reduction in carbon-di-oxide [CO2] emission cost. Advancement in electric vehicles is extensively happening and one such concept is Battery management system [BMS] in Battery Electric vehicle. In electric vehicle battery, there are many types of batteries and from the literature survey Lithium Ion Battery are more suitable because it is advantageous in weight, cost, energy density and lots of aspects. Battery might be overcharged or going to undergo faults. Hence a reliable management system is required to control the Electric vehicle [EV]. In this paper two battery charge estimation models namely, open circuit voltage and Kalman filter has been considered. From the simulation results obtained it is found that data retrieval is difficult in open circuit voltage method can be achieved using Kalman filter and found out to be satisfactory.

[1] Wu, C.; Zhu, C.; Ge, Y.; Zhao, Y. A Review on Fault Mechanism and Diagnosis Approach for Li-Ion Batteries. J. Nanomater. 2018, 1–9. [CrossRef] [2] Liu, Z.; Ahmed, Q.; Zhang, J.; Rizzoni, G.; He, H. Structural analysis based sensors fault detection and isolation of cylindrical lithium-ion batteries in automotive applications. Control Eng. Pract. 2016, 52, 46–58. [CrossRef] [3] Liu, K.; Liu, Y.; Lin, D.; Pei, A.; Cui, Y. Materials for lithium-ion battery safety. Sci. Adv. 2018, 4, eaas9820. [CrossRef] [PubMed] [4] Kong, L.; Li, C.; Jiang, J.; Pecht, M. Li-Ion Battery Fire Hazards and Safety Strategies. Energies 2018, 11, 2191. [CrossRef] [5] Wei,J.;Dong,G.;Chen,Z.Model bas edfault diagnosis of Lithium ion battery using strong tracking Extended Kalman Filter. Energy Procedia 2019, 158, 2500–2505. [CrossRef] [6] Kim, H.; Shin, K.G. Modeling of externally-induced/common-cause faults in fault-tolerant systems. In Proceedings of the AIAA/IEEE Digital Avionics Systems Conference. 13th DASC, Phoenix, AZ, USA, 30 October–3 November 1994; pp. 402–407.
[7] Doughty,D.;Roth,E.P.AGeneral Discussion of Li Ion Battery Safety. Electro chem. State of Charge. Interface2012,21,37–44.
[8] Lu, L.; Han, X.; Li, J.; Hua, J.; Ouyang, M. A review on the key issues for lithium-ion battery management in electric vehicles. J. Power Sources 2013, 226, 272–288. [CrossRef] [9] Venkatasubramanian, V.; Rengaswamy, R.; Yin, K.; Kavuri, S.N. A review of process fault detection and diagnosis. Comput. Chem. Eng. 2003, 27, 293–311. [CrossRef] [10] Xiong, R.; Yu, Q.; Shen, W. Review on sensors fault diagnosis and fault-tolerant techniques for lithium ion batteries in electric vehicles. In Proceedings of the 2018 13th IEEE Conference on Industrial Electronics and Applications (ICIEA), Wuhan, China, 31 May–2 June 2018; pp. 406–410.