Around the world, SDVs or software-defined vehicles are one of the two trends driving the design of new vehicles, the other being EVs or electric vehicles. As a result, vehicle design is undergoing a major transformation. From features and capabilities that were so far defined by hardware, they are now changing over to those being defined by software. This opens up newer opportunities resulting in agile developments, fast and continual improvements, and remote maintenance.
SDVs are ushering in a new approach to the development of vehicles. In turn, that is enabling improvements in the vehicle over time, based on in-depth access to the vehicular data in real time. Cloud processing and machine-learning training is leading to updates over the air for improving the software and related machine-learning models. Along with this continuous deployment and integration, engineers are able to use model-based design tools more effectively for improving and developing software algorithms that, in turn, help to run the vehicles more efficiently.
As a result, carmakers over the world are investing hugely in vehicle electrification for helping to reduce greenhouse gases. They are offering their customers vehicles with acceptable driving ranges along with easy access to charging stations. Many are committing to transitioning their fleets from ICE or internal combustion engines to EVs over the next decades. This is resulting in the swift deployment of EVs. Furthermore, the effect of this shift to a more software-centric and electric future is bringing newer challenges to the automobile industry.
The major beneficiary of this change is the EV motor. With the industry moving to the SDV approach, there is faster access to vehicular data that can monitor the aging and performance of the EV motor. Powerful automotive microcontrollers now support newer features over time, while the deployment of software upgrades is available through wireless updates. This makes the software-defined EV motor a dynamic product that keeps evolving and improving over time. It takes advantage of in-vehicle data in real-time, supporting cloud development along with enhancing features.
Changing over to a software-defined EV motor design affects all the stages of development of the control systems of the EV motor. Not only does this enable faster cycles of development, but also helps enhance the performance, while monitoring for maintenance needs, thereby extending the system’s lifetime.
High-level modeling tools are the trend in motor control design. Designers use modeling tools like Simulink and MATLAB for concentrating on using their key expertise in controlling the EV motor and systems, rather than on programming. This is because modeling tools operate at the algorithm level, where the designers can optimize them to improve vehicular performance and efficiency.
Using modeling tools results in three significant advantages—flexibility, safety, and speed. Designers use modeling tools to test algorithms and quickly analyze software, rather than depend on evaluation through hardware integration. Not only does this bring in flexibility, but also speed when designing the control module of EV motors. For designers, developing at the algorithm level is especially useful when developing strategies for the smooth control of a motor.
