Embedded Instrumentation System Using Acquisition Mechanism for BLDC-Powered Electric Vehicle
The primary component of an electric vehicle is the electric motor. In order for the motor to operate properly, some measurement and data acquisition are required for monitoring and controlling its performance. For this purpose, an embedded system is developed and attached to the vehicle. This paper presents the design and implementation of an embedded instrumentation system that includes a data acquisition device, data processor, and data display. A complete prototype-scale electric vehicle was developed and equipped with an embedded instrumentation system. A Brushless DC (BLDC) motor is employed as prime-mover taking power from a 10-Ah Battery. The input parameter is determined by the vehicle’s throttle opening, and the output variables are measured and processed. For the purpose of data acquisition, the system relies on Arduino and Raspberry Pi as processing and monitoring devices. The data and information are displayed on the vehicle dashboard to indicate the real-time vehicle performance and some related information. These include speed, power, motor temperature, distance achieved, and estimated distance that can still be reached with the remaining battery capacity. The data and information are graphically and numerically displayed, which would be useful for steering that enhances system efficiency. The system was tested in the lab and real system, where it demonstrated fine accuracy. The average deviations of the electrical data displayed in the instrumentation system with those given by the standard meter are 0.25 Volt, 0.03 Amp, and 0.43 Watt for voltage, current, and power, respectively. From a mechanical standpoint, the average deviations of speed and torque are 1.2876 km/h and 1.218*10-4 Nm, respectively. The contributions of this research are the development of a complete system to be operated in real conditions, and validation of the displayed information with standard measurement and manual calculation.
Electric Vehicle;Measurement and Acquisition;Real-time performance;Efficiency
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