Design and analysis of capacity models for Lithium-ion battery

被引:49
|
作者
Garg, Akhil [1 ]
Peng, Xiongbin [1 ]
My Loan Phung Le [2 ]
Pareek, Kapil [3 ]
Chin, C. M. M. [4 ]
机构
[1] Shantou Univ, Intelligent Mfg Key Lab, Minist Educ, Shantou, Peoples R China
[2] Viet Nam Natl Univ Ho Chi Minh City VNUHCM, Univ Sci, Fac Chem, Dept Phys Chem,Appl Phys Chem Lab, Ho Chi Minh City, Vietnam
[3] Malaviya Natl Inst Technol, Ctr Energy & Environm, JLN Marg, Jaipur 302017, Rajasthan, India
[4] Univ Nottingham, Dept Mech Engn, Malaysia Campus, Semenyih, Malaysia
关键词
Battery modelling; Electric vehicle; Genetic programming (GP); Complexity; Battery capacity; Temperature; SRM; MULTIPLE ROBOTIC MANIPULATORS; ELECTRIC VEHICLE; NEURAL-NETWORKS; CO2; PIPELINE; HYBRID; ROBUST; STRATEGIES; MANAGEMENT; EFFICIENCY; STEPWISE;
D O I
10.1016/j.measurement.2018.02.003
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Past studies on battery models is focussed on formulation of physics-based models, empirical models and fusion models derived from the battery pack data of electric vehicle. It is desirable to have an explicit, robust and accurate models for battery states estimation in-order to ensure its proper reliability and safety. The present work conducts a brief survey on battery models and will propose the evolutionary approach of Genetic programming (GP) for the battery capacity estimation. The experimental design for GP simulation comprises of the inputs such as the battery temperature and the rate of discharge. Further, the seven objective functions in GP approach is designed by introducing the complexity based on the order of polynomial. This step will ensure the precise functions evaluation in GP and drives the evolutionary search towards its optimum solutions. The design and analysis of the GP based battery capacity models involves the statistical validation of the seven objective functions based on error metrics with 2-D and 3-D surface plots. The results conclude that the GP models using Structural risk minimization (SRM) objective function accurately estimate the battery capacity based on the variations of the inputs. 2-D and 3-D surface analysis of the GP model reveals the increasing-decreasing nature of temperature-battery capacity curve with temperature the dominant input. The battery capacity model obtained using SRM as an objective function in GP is robust and thus can be integrated in the electric vehicle system for monitoring its performance and ensure its safety.
引用
收藏
页码:114 / 120
页数:7
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