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Most times in ECU system function testing, the sensor input signals are directly set to a known value in order to drive the corresponding software variable to within a range of an expected value. This works only if the transfer function from the physical signal input to the software variable is well defined such as the measurement on MAP, A/C pressure, etc. Nevertheless, there are times the transfer function is not clearly defined and it is difficult to drive the software variable to an expected value. One example is throttle position sensor (TPS) test in an electronic throttle control (ETC) system, where TPS is not directly driven by the driver accelerator pedal sensor (APS) and it is very difficult to get TPS to an expected range by only changing APS. This paper introduces a method to use feedback in an HIL based ECU testing system to control outputs to an expected range. In this case study, the signal to be controlled is connected back to the HIL system to provide feedback.

To confirm the correct operation and detect the potential errors in the ever more complicated automotive ECU application software are very challenging. This paper presents a new approach to detect potential ECU application software abnormal behavior based on the Mahalanobis Distance, the Mahalanobis-Taguchi System, and vehicle driving data playback capability with a simulator. Vehicle driving data is recorded by instrumentation calibration tools and played back on the test bench to stimulate the ECU. In our study, the normal behavior is characterized by the Mahalanobis Distance (MD), which is calculated from the data set logged while playing back the recorded vehicle maneuvers while the ECU is flashed with “baseline software” that was believed to be error free. Then the MDs were calculated from a new data set logged while playing back the same vehicle maneuvers while the ECU was flashed with the new software.