Speed up motor ECU design with HIL simulation

These days, an enormous number of ECUs are incorporated in automotives to manage expanded functionality and advanced controls in the vehicle. In a hybrid vehicle, the motor ECU plays an even more complicated role as it manages the interaction between the conventional engine and the electric motor, along with its power systems. Development can be accelerated substantially through the application of hardware-in-the-loop methods.

Fuji Heavy Industries, parent company of carmaker Subaru, set out to develop its first hybrid vehicle—the Subaru XV Crosstrek Hybrid. It was a preliminary attempt to deliver a production model hybrid vehicle targeting both domestic Japanese and North American markets. Engineers had developed a motor ECU for an earlier hybrid prototype, but the component did not meet the rigorous requirements to take a vehicle to market. For the production model vehicle, the ECU needed various control functionalities to prevent damage to the vehicle body and to ensure driver and passenger safety under various operating conditions, even scenarios that would be impossible or impractical to test on physical hardware.

For example, under icy driving conditions, a wheel can experience a sudden loss of traction. During acceleration this can cause a dramatic increase in motor speed and needs to be handled safely. However, this safety behaviour cannot be physically reproduced on a dynamometer and is time consuming and difficult to reproduce on a test track. Since complex control algorithms for specific safety conditions like this need to be developed and verified, the testing needed to account for outlying operating conditions to satisfy the quality level required for a production model vehicle.

The challenge was to use automated testing to develop a new verification system that satisfied the control quality level required for the motor electronic control unit (ECU) in Subaru's first production model hybrid vehicle, Subaru XV Crosstrek Hybrid, and to create strenuous test conditions that are difficult to achieve using real machines.

Engineers connected the ECU to a real-time electric motor simulation to test and verify a variety of conditions, including the extreme outliers that may otherwise break the system in traditional mechanical testing. They developed a mechanism to sufficiently confirm this software simulation approach with three primary goals for successful testing:

 • Verify ECU functionality in various conditions, including extreme environments not easily created or replicated
 • Map test cases to requirements to ensure complete test coverage
 • Perform regression tests with ease to quickly validate design iterations
To achieve these goals, the engineering team used a V-diagram approach to launch the design and verification process (figure 1). The diagram describes a phased methodology for embedded software design and deployment validation, including test points at each stage. In multiple steps of the design process, the team needed the hardware-in-the-loop (HIL) system to verify the motor ECU against a real-time motor simulation that accurately represented the actual vehicle motor. Additionally, using the HIL system, our engineers could meet traceability requirements by recording test results automatically and automating regression tests when an ECU change was made.

The new verification system built consists of a real motor ECU and the HIL system that simulates motor operations (figure 2). The HIL system can represent any operating condition of the motor by setting physical parameters such as inductances or resistances. It can also set parameters of the power electronics, including fault conditions or test scenarios such as combinations of load torque and desired rotating speed.

By simply changing a parameter in the middle of the test, the HIL system can easily simulate complex test scenarios like the previous loss of traction example or even a power electronics fault in the inverter that would destroy physical hardware. When the operator requests a test pattern, the HIL system responds the way a real motor would, and the overall system response can then be cross-referenced with expectations to validate that the controller safely handles the test case.