Innovative method for state of energy estimation based on improved Cubature Kalman filter

As the increasing concern of driving ranges for electric vehicles, the precision of state of energy (SOE) estimation contributes to the better performance of battery management. In this article, an innovative method based on 5th-order simplex square-radius cubature Kalman filter is developed to achieve the precise and robust estimation for SOE on electric vehicles. Based on second-order equivalent circuit model and particle-swarm-optimization algorithm, the implementation helps the validation of SOE estimation. The max error of SOE estimation under stable condition is less than 3%, and that for dynamic stress test condition is under 4%. Moreover, the robustness is investigated based on diverse deviations on initialization, delivering the future potential applications on embedded system on cloud-controlling.

[1]  Tae Gyun Kim,et al.  Data-efficient parameter identification of electrochemical lithium-ion battery model using deep Bayesian harmony search , 2019, Applied Energy.

[2]  Dafang Wang,et al.  A lithium-ion battery electrochemical–thermal model for a wide temperature range applications , 2020 .

[3]  Yuejiu Zheng,et al.  Parameter sensitivity analysis and simplification of equivalent circuit model for the state of charge of lithium-ion batteries , 2020 .

[4]  Guangzhong Dong,et al.  A method for state of energy estimation of lithium-ion batteries based on neural network model , 2015 .

[5]  Michael Fowler,et al.  Effect of integrating the hysteresis component to the equivalent circuit model of Lithium-ion battery for dynamic and non-dynamic applications , 2020 .

[6]  Chunbo Zhu,et al.  A physics-based fractional order model and state of energy estimation for lithium ion batteries. Part I: Model development and observability analysis , 2017 .

[7]  Zonghai Chen,et al.  A novel method for lithium-ion battery state of energy and state of power estimation based on multi-time-scale filter , 2018 .

[8]  Hua Yang,et al.  Adaptive model parameter identification for lithium-ion batteries based on improved coupling hybrid adaptive particle swarm optimization- simulated annealing method , 2021 .

[9]  Sijia Liu,et al.  State of Energy Estimation of Lithium Titanate Battery for Rail Transit Application , 2017 .

[10]  Xianguo Li,et al.  A modeling and experimental study of capacity fade for lithium-ion batteries , 2020 .

[11]  Datong Qin,et al.  Lithium-ion battery modeling and parameter identification based on fractional theory , 2018, Energy.

[12]  S. Choi,et al.  A physics-based distributed-parameter equivalent circuit model for lithium-ion batteries , 2019, Electrochimica Acta.

[13]  Michael Pecht,et al.  Aging modes analysis and physical parameter identification based on a simplified electrochemical model for lithium-ion batteries , 2020 .

[14]  Yingfeng Cai,et al.  A novel resistor-inductor network-based equivalent circuit model of lithium-ion batteries under constant-voltage charging condition , 2019, Applied Energy.

[15]  Daniel-Ioan Stroe,et al.  A novel charged state prediction method of the lithium ion battery packs based on the composite equivalent modeling and improved splice Kalman filtering algorithm , 2020, Journal of Power Sources.

[16]  W. Marsden.  I and J , 2012 .

[17]  Jianhua Xu,et al.  State of energy estimation for a series-connected lithium-ion battery pack based on an adaptive weighted strategy , 2021 .

[18]  Zonghai Chen,et al.  Model-based State-of-energy Estimation of Lithium-ion Batteries in Electric Vehicles , 2016 .

[19]  Ragab A. El-Sehiemy,et al.  Parameter identification and state-of-charge estimation for lithium-polymer battery cells using enhanced sunflower optimization algorithm , 2020 .

[20]  Chunbo Zhu,et al.  Parameter identification of electrolyte decomposition state in lithium-ion batteries based on a reduced pseudo two-dimensional model with Padé approximation , 2020 .

[21]  Guangzhong Dong,et al.  An online model-based method for state of energy estimation of lithium-ion batteries using dual filters , 2016 .