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The article presents an analysis of the optimal control of speed and regenerative braking in an electric vehicle (EV). The presence of the continuous generating power is one of the major challenges for battery charging of electric vehicle. In order to meet the demand of continuous power, electric vehicles are driven by solar PV arrays. Initially, maximum power extraction (MPPT) is assessed from a solar photovoltaic (PV) array using the P&O method. The outputs of the solar PV array are integrated with electric vehicles. Such integration creates the problem of maintaining the power quality. The existing methods also address the issue of optimal speed and torque control with high transients and more settling time. In this article, an electric vehicle is modeled first and then operated in regenerative braking mode. To address the shortcomings of existing methods, the linear quadratic regulator (LQR) method is used; then, fuzzy logic controller (FLC)-based LQR is used for optimal speed and torque control during electric vehicle regenerative braking. In terms of reduced settling time and improved peak overshoot, optimal speed and regenerative torque of electric vehicles are better realized with LQR-based FLCs than with LQR controllers. In addition to this, stopping speed characteristics with various electrical parameters (voltage, current, and flux) have been analyzed with different methods in which LQR-based FLC shows its dominance to attain zero speed in regenerative mode with more sharp characteristics. [ABSTRACT FROM AUTHOR]