HL Mando Automates Durability Testing for Drive-by-Wire Steering

Custom Apps Enhance Safety Testing for EVs and Autonomous Vehicles

“I searched a lot of open-source programming languages, but they were impossible to use without specialized knowledge. Then I saw Vehicle Network Toolbox in MATLAB, and it contained all the features I wanted.”

Key Outcomes

  • MATLAB and Simulink enabled non-software engineers to develop domain-specific programs for durability testing
  • Vehicle Network Toolbox enabled hands-off and remote execution of durability testing
  • MATLAB improved the efficiency of pre- and post-processing durability test data, and custom apps developed in MATLAB provided a cost-effective solution to advance testing
Video length is 28:40

HL Mando is a global leader in developing safety components for EV and autonomous driving vehicles, including drive-by-wire steering solutions. Testing the durability of these steering systems is paramount to safety but can be challenging when compared to testing traditional mechanical steering systems. For example, drive-by-wire steering requires digital sensors to detect the driving environment or torque applied while turning the wheel.

As testing the durability of these sensors can be time-intensive and costly, HL Mando engineers sought an automated solution and found that MATLAB® and Simulink® provided an answer. The team used App Designer and Vehicle Network Toolbox™ to design apps in-house without the need for prior software engineering experience.

These apps used Vehicle Network Toolbox XCP communication features to enable real-time monitoring of testing data such as load data, geometric data from the vehicle’s environment, and stress data. Vehicle Network Toolbox was used to measure the internal torque value from drive-by-wire sensors, as well as the temperature and internal calibration value in the ECU. Additionally, Data Acquisition Toolbox™ was used to get external signals, such as accelerometer readings and chamber temperature. MATLAB also helped pre- and post-process the data and analyze it to extract parameters and waveforms from the tests. These solutions improved the reliability of the testing and helped make it more cost-effective.