CAPACITY LOSS ESTIMATION FOR LI-ION BATTERIES BASED ON A SEMI-EMPIRICAL MODEL: MATHEMATICAL SIMULATION OF ADJACENT-COUPLING AMMONIA ABSORPTIVE REACTOR

Understanding battery capacity degradation is instrumental for designing modern electric vehicles. In this paper, a Semi-Empirical Model for predicting the CapacityLoss of Lithium-ion batteries during Cycling and Calendar Aging is developed. In order to predict the Capacity Loss with a high accuracy, battery operation datafrom different test conditions and different Lithium-ion batteries chemistries were obtained from literature for parameter optimization (fitting). The obtained modelswere then compared to experimental data for validation. Our results show that the average error between the estimated Capacity Loss and measured Capacity Loss isless than 1.5% during Cycling Aging, and less than 2% during Calendar Aging. An electric mining dumper, with simulated duty cycle data, is considered as an application example.Understanding battery capacity degradation is instrumental for designing modern electric vehicles. In this paper, a Semi-Empirical Model for predicting the Capacity Loss of Lithium-ion batteries during Cycling and Calendar Aging is developed. In order to predict the Capacity Loss with a high accuracy, battery operation data from different test conditions and different Lithiumion batteries chemistries were obtained from literature for parameter optimization (fitting). The obtained models were then compared to experimental data for validation. Our results show that the average error between the estimated Capacity Loss and measured Capacity Loss is less than 1.5% during Cycling Aging, and less than 2% during Calendar Aging. An electric mining dumper, with simulated duty cycle data, is considered as an application example