An Advanced Ultracapacitor SOC Concept to Increase Battery Life Span of Electric Vehicles

Abstract

The lifecycle of the battery is mostly exaggerated by the overall energy throughput speed, accumulated heat, and rapid utilization. The adequate utilization and operation of the battery are improved in the flexibility range by the permutation of the battery and the ultracapacitor in the electric vehicle. The overall system performance is determined by the energy management system which plays a significant part in dual-energy storage systems. The major intent of this research is to enhance the performance of electric vehicles which is achieved by maintaining the charge of depleting and charge of sustaining level in the battery and the state of charge in the ultracapacitor. The proposed method controls the state of charge of the battery and the ultracapacitor to make sure the availability of charge throughout the complete settling rate of the battery in the electric vehicle. To attain this condition, the dual converter-based two-stage Artificial Neural Network is initialized. In the first stage of the Artificial Neural Network, the charge sustained in the ultracapacitor is controlled during acceleration which completely depends on the velocity of the vehicles. In contrast to that, in the second stage of the Artificial Neural Network, charge depleting in the UC is trained by connectionless with varying vehicle velocities at deceleration rates. The production and investigation of parameters are not effectively optimized using conventional methods hence the herding and howling characters are combined together and proposed energetic and problem-solving optimization-based metaheuristic algorithm that efficiently tunes the parameters. The SOC rate of the battery for three driving cycles using the proposed method follows FTP75 71.309% at 2474th s and J1015 attained 90.840% at 660th s and the UDDS attained 81.647%. The SOC rate of the Ultracapacitor for three driving cycles using the proposed method follows FTP75 63.518% at 2474 s, J1015 attained 69.332% at 660 s and UDDs attained 67.049%. The experimental arrangement is executed in MATLAB-Simulink. The state of charge of the battery and the ultracapacitors for the varying drive cycles as FTP75, J1015, and UDDS are experimentally validated and verified with the prevailing methods. The developed method reveals better performance for enhancing the lifespan of the power storeroom system in electric vehicles.