title: Tuning of Kalman filter parameters via genetic algorithm for state-of-charge estimation in battery management system.
abstract: In this work, a state-space battery model is derived mathematically to estimate the state-of-charge (SoC) of a battery system. Subsequently, Kalman filter (KF) is applied to predict the dynamical behavior of the battery model. Results show an accurate prediction as the accumulated error, in terms of root-mean-square (RMS), is a very small value. From this work, it is found that different sets of Q and R values (KF's parameters) can be applied for better performance and hence lower RMS error. This is the motivation for the application of a metaheuristic algorithm. Hence, the result is further improved by applying a genetic algorithm (GA) to tune Q and R parameters of the KF. In an online application, a GA can be applied to obtain the optimal parameters of the KF before its application to a real plant (system). This simply means that the instantaneous response of the KF is not affected by the time consuming GA as this approach is applied only once to obtain the optimal parameters. The relevant workable MATLAB source codes are given in the appendix to ease future work and analysis in this area.
authors.affiliation: Department of Electrical and Electronic Engineering, Xi'an Jiaotong-Liverpool University, No. 111, Ren'ai Road, HET, SIP, Suzhou, Jiangsu 215123, China.
authors.forename: T O
authors.initials: TO
authors.lastname: Ting
authors.affiliation: Department of Computer Science and Software Engineering, Xi'an Jiaotong-Liverpool University, No. 111, Ren'ai Road, HET, SIP, Suzhou, Jiangsu 215123, China ; Department of Computer Science, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul 120-749, Republic of Korea.
authors.forename: Ka Lok
authors.identifier: 0000-0002-5787-4716
authors.initials: KL
authors.lastname: Man
authors.affiliation: Department of Electrical and Electronic Engineering, Xi'an Jiaotong-Liverpool University, No. 111, Ren'ai Road, HET, SIP, Suzhou, Jiangsu 215123, China.
authors.forename: Eng Gee
authors.initials: EG
authors.lastname: Lim
authors.affiliation: Department of Electrical and Electronic Engineering, Xi'an Jiaotong-Liverpool University, No. 111, Ren'ai Road, HET, SIP, Suzhou, Jiangsu 215123, China.
authors.forename: Mark
authors.identifier: 0000-0002-7874-2376
authors.initials: M
authors.lastname: Leach
mesh_terms: D000465:Algorithms; D004736:Energy-Generating Resources; D008962:Models, Theoretical