Authors - Febin Koshy Jacob, Indranil Bose, Sarika D Tavhare, Sandhya Anilkumar Abstract - Modern automotive Electronic Control Unit (ECU) systems demand robust and accurate validation frameworks to address increasing system complexity while minimizing manual test effort and development cost. This paper novels an automated Hardware-in-the-Loop (HIL) testing framework for validation of automotive systems, with a primary focus on automated waveform pattern analysis method. The framework integrates a dSPACE real-time interface with a hardware test bench and algorithm developed using a MATLAB-based simulation model of the Body Control Module (BCM) to generate and analyze input signals. Python-based automation scripts are utilized for test execution control, synchronized data acquisition, and automated result analysis, ensuring repeatable and scalable testing across multiple application domains. The core contribution is a reference-driven waveform comparison methodology, where signals captured from the Device Under Test (DUT) are evaluated against predefined golden reference waveforms. The approach quantifies Root Mean Square Error (RMSE) percentage and timing deviations across individual channels, enabling precise detection of mismatches in waveform sequences. The framework is demonstrated through automotive tail lamp animation pattern validation, where output sequences are compared against reference waveforms for accuracy and robust assessment. Additionally, the solution is extendable to electric vehicle subsystems such as Battery Management Systems (BMS), Traction Motor Control Units (TMCU), and Off-Board Chargers (OFBC), supporting both dynamic and steady-state validation such as torque-speed curve, Battery profile testing, Sensor accuracy etc. The implementation achieves approximately 45.8% automation of test cases and reduces overall validation time by about 41.2%, resulting in improved repeatability, reduced manual intervention, and faster development cycles, ultimately enabling faster time-to-customer and providing a scalable and efficient solution for modern automotive and electric vehicle system validation.
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