Electric vehicle battery modelling and performance comparison in relation to range anxiety

In electric vehicle, rechargeable battery served as energy source for all its system operation which include electric motor for propulsion system and also other auxiliary components. Therefore, it becomes an important issue to be tackled in EV technology in order to enhance the battery energy capacity for long range operation. In general public view, people tend to be very concern in purchasing the electric car. One of the concerns lies on the question of how far they can travel with only battery for their car propulsion means. Therefore, this study tries to investigate the relation between battery types and the range anxiety faces by electric car makers. The investigations reveals that, Li-ion as the battery with high energy density cover more area or distance travel

Hybrid pid and pso-based control for electric power assist steering system for electric vehicle

Electric power assist steering (EPAS) system provides an important significance in enhancing the driving performance of a vehicle with its energy-conserving features. This paper presents a hybrid PID (Proportional-Integral-Derivative) and particle swarm optimization (PSO) based control scheme to minimize energy consumption for EPAS. This single objective optimization scheme is realized using the PSO technique in searching for best gain parameters of the PID controller. The fast tuning feature of this optimum PID controller produced high-quality solutions. Simulation results show the performance and effectiveness of the hybrid PSO-PID based controller as opposed to the conventional PID controller

Energy consumption optimization with PSO scheme for electric power steering system

Energy management in Electric Vehicle (EV) technology is very important as the energy source of all its system operations are solely relying on the battery. The unique characteristic of Electric Power Assist Steering (EPAS) system provides a way in realizing minimum energy consumption in EV subsystem. The controller in the EPAS system need to be tuned with the optimal performance setting so that less current is needed for its optimum operation. In this paper, Particle Swarm Optimization (PSO) algorithm is implemented as tuning mechanism for PID controller. The aim of this hybrid controller is to minimize energy consumption of the EPAS system in EV by minimizing the assist current supplied to the assist motor. The PSO searching method will search for the best gain parameters of the PID controller and providing the fast tuning feature that distinguish it from the conventional trial and error method. Simulation results shows the performance and effectiveness of using PSO algorithm for PID tuning