Development and Validation of a Low Cost Data Acquisition System for Automotive Engine Sensors

This research presents the development and validation of an ESP32-based data acquisition system for an automotive engine stand in vocational engineering education. Conventional use of multimeters and oscilloscopes is restricted to single-channel, non-synchronised measurements, limiting students’ ability to analyse dynamic engine-sensor behaviour. The proposed system interfaces with eight automotive sensors namely MAP, TPS, IAT, ECT, O₂, CKP, CMP, and knock, through dedicated signal-conditioning circuits and an ESP32 microcontroller. Firmware written in C/C++ using the Arduino IDE enables multi-channel sampling, real-time clock time-stamping, Bluetooth communication, and simultaneous logging to microSD and PLX-DAQ/Excel on a personal computer, together with Android-based monitoring. System performance was evaluated on a K3-VE engine stand by comparing measured voltages and waveforms with digital-multimeter and oscilloscope readings at idle, 2000, and 3000 rpm. For TPS, MAP, ECT, and IAT, the mean absolute percentage error generally ranges from 0% to about 3%, while the O₂ sensor shows larger errors of approximately 1–8% but still reproduces the correct operating range and trends. CKP, CMP, and knock channels successfully capture the essential digital and filtered waveforms for timing and knock demonstrations. These findings indicate that the platform provides sufficiently accurate, real-time multi-sensor monitoring for automotive diagnostics training and offers a scalable basis for future IoT-oriented instructional tools.