- Admin
- January 22, 2025
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Case Study
GUI for BLDC Motor Control
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Client
A US-based Tier-1 Semiconductor company approached Ignitarium to modernize its motor control GUI tool to resolve problems and enhance features. The tool was to be built for a target audience of system designers / end customers who use the chip / modules offered by this semiconductor company. The UI and the functionalities enable the end users to rapidly prototype and accelerate the system design process.
Scope
• Design and develop an intuitive UI application to support novice to expert level user of the customer's boards
• Read and Write operations to shadow and EPROM registers
• Auto detection of the board when the application is started
• Self-healing and recovery from configuration faults
• Ability to integrate Matlab scripts
• Support multiple user OS platforms
• Seamless integration of newer board models
Challenges
The customer’s existing GUI solution had a few limitations
• Non intuitive and dated design
• Complex flow for novice user
• Performance issues while plotting several parameters at once
• Support for newer version of boards required development effort
The customer wanted to add the following features
• Multi-platform compatibility
• Matlab scripting integration
• Framework to add newer board models of the customer without code change
Solution
Our end-to-end expertise in various embedded automotive platforms coupled with our strength in the digital domain played a key role in solution development.
• The application’s hardware needs, dependencies on firmware, software libraries, duration of model loading and inferencing, triggers for model execution, interpretation of results from execution, storage and transmission of results are characterised. Profiling is done using software tools to measure CPU cycles, memory footprint and the outcome is an accurate assessment of platform and pipeline component requirements.
• Packaging environment requirements were defined considering the technology stacks involved in development and deployment. The automotive platform in use defines the need for kernel libraries, container runtimes (runc / crun), machine / deep learning / data processing libraries (tensorflow / scikit / jax / numpy) to build containers (docker / podman) as pipeline components and the API specifications for interfaces to other middleware components.
• Deployment environment preparation factored firmware needs including virtualisation and container stacks on the automotive platforms. Interfaces collect input from data packages and send output to the data sinks (local storage or telematics controller).
Business Impact
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Enhancing the design-in win / loss ratio: An effective, functional and intuitive UI for the semiconductor company’s end customers to design systems seamlessly and rapidly.
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Enabled faster time to market through a flexible low code solution that makes it easy to onboard new variants from the family of boards / hardware kits.