Collecting Big Data from Automotive ECUs beyond the CAN Bandwidth for Fault Visualization

Abstract

A hardware-in-the-loop (HiL) test is performed to verify the software functions mounted on automotive electronic control units (ECUs). However, the characteristics of HiL test limit the usage of common debugging techniques. Meanwhile, the logs of how the program uses memory can be utilized as debugging information collected by the controller area network (CAN). However, when the 32 KB memory is observed with 10 ms period, about 96% of the data on each cycle is lost, since the CAN only can transfer 1.25 KB of data at each cycle. Therefore, to overcome the above limitations, in this study, the memory is divided into multiple regions to transmit generated data via CAN. Next, the simulation is repeated for the each divided regions to obtain the different areas in each simulation. The collected data can be visualized as update information in each cycle and the cumulative number of updates. Through the proposed method, the ECU memory information during the HiL test was successfully collected using the CAN; the transmission is completed without any loss of data. In addition, the data was visualized in images containing the update information of the memory. These images contribute to shortening the debugging time for developers and testers.