Recently, due to rapid growth in electric vehicle motors, used and power electronics have received a lot of concerns. 3ϕ induction motors and DC motors are two of the best and most researched electric vehicle (EV) motors. Developing countries have refined their solution with brushless DC (BLDC) motors for EVs. It is challenging to regulate the 3ϕ BLDC motor’s steady state, rising time, settling time, transient, overshoot, and other factors. The system may become unsteady, and the lifetime of the components may be shortened due to a break in control. The marine predator algorithm (MPA) is employed to propose an e-vehicle powered by the maximum power point tracking (MPPT) technique for photovoltaic (PV). The shortcomings of conventional MPPT techniques are addressed by the suggested approach of employing the MPA approach. As an outcome, the modeling would take less iteration to attain the initial stage, boosting the suggested system’s total performance. The PID (proportional integral derivative) is used to govern the speed of BLDC motors. The MPPT approach based on the MPA algorithm surpasses the variation in performance. In this research, the modeling of unique MPPT used in PV-based BLDC motor-driven electric vehicles is discussed. Various aspects, which are uneven sunlight, shade, and climate circumstances, play a part in the low performance in practical scenarios, highlighting the nonlinear properties of PV. The MPPT technique discussed in this paper can be used to increase total productivity and reduce the operating costs for e-vehicles based on the PV framework.

Fault detection and identification in a solar Photovoltaic (PV) systems are one of the crucial task in recent days for ensuring both reliability and safety measures. The fault occurrence in the PV cell will affect the output power, and can reduce the efficiency of its characteristics. The fault in PV cell can identify by using the thermal scan method manually. Arrangement of the proposed setup regularly is not possible to monitor due to the hardware installation of several equipment, it took more time to test, and validate the affected PV cells prediction less accuracy while doing in manual testing. In order to solve these issues, this paper intends to propose a novel algorithm, named as Truncated Arrangement of Active Cell (TAAC) structure for accurately detecting the PV faults. This technique is used to analyze the PV cell aging condition and to enhance the PV characteristics. Typically, the improvement in a cell arrangement provides an optimal solution for efficient fault detection. Moreover, the TAAC architecture computes the optimal solution for a PV output terminal based on the PV cell parameters and variation of temperature measures. Also, a Kalman filtering technique is employed to extract the features that are used to improve the detection process. The major advantages of this structure are, it enhance the lifetime of PV cell and stores the maximum power for a long time usage. The experimental results evaluate the performance of this technique by using various measures such as false alarm rate, misclassification rate, misdetection rate, and prediction rate. Furthermore, some of the existing techniques are compared with the proposed technique for proving its superiority.