As vehicle electronics and electrical distribution systems become increasingly complex, requirements need to be clear, complete, and consistent. In traditional hand-coding workflows, ambiguous or conflicting requirements are often discovered late in the development process, leading to schedule or cost overruns.

Handwritten code for controllers with hundreds of inputs and outputs and sophisticated state logic is difficult to maintain and reuse. “In the past, as we implemented an engineering change request in one area, we had a difficult time predicting the types of issues we were introducing in the rest of the system,” recalls Jinming Yang, principal engineer at Lear.

Lear adopted Model-Based Design for the design, verification, and implementation of dozens of body electronics systems.

In one BCM project, Lear engineers analyzed customer requirements and partitioned the overall system into components such as interior and exterior lighting, battery management, and vehicle starting control.

The team used MATLAB^®, Simulink^®, and Stateflow^® to develop fully functional behavioral models, including all required inputs and outputs, for each component.

To conduct early unit testing, the engineers used the Signal Builder block in Simulink to generate test stimuli and incorporate them into the models. The team also used Simulink to develop plant models for functional testing.

Using Simulink Check™, Simulink Coverage™, and Simulink Requirements™ the team analyzed model coverage and continued refining test cases, designs, and requirements until they reached satisfactory model coverage levels, including decision coverage and modified condition/decision coverage (MC/DC).

After verifying nearly 400 unit models, the team used Embedded Coder^® to generate C code. They verified this code via software-in-the-loop (SIL) tests that reused the test cases generated for the unit model tests.

Lear engineers integrated the generated code for each unit model into 20–30 feature-level components, which were in turn integrated into a complete system model. The team met with the customer and ran simulations of the components and the complete model to resolve ambiguities in the original design specification.

The group used MATLAB scripts to automate the conversion of test cases into test vectors for hardware-in-the-loop (HIL) and vehicle-based testing. They wrote additional MATLAB scripts to import and analyze the test results from the hardware.

The ability to share models enabled Lear to extend the workday across a distributed team. In some cases, design changes made by Lear engineers in North America were tested the same night by colleagues in Asia.

On a separate project for an international customer, issues with translating technical terminology made it challenging for Lear engineers to understand a particular requirement. “We used a Simulink model including a Signal Builder block to visualize different timing options, and the customer immediately selected the one they wanted,” notes Bauman. “Opening that line of communication was vital to the project.”