Trust, speed, and decisive action: A behind-the-scenes look at AI-driven EV design

Systems are typically composed of multiple elements that work together to achieve a specific purpose. But, according to Rzepecki, when trying to achieve more optimal system-level designs for electric motors and EV powertrains (unlike single stand-alone components), “as you increase the number of parameters (variables) included in the computation, complexity increases exponentially,” creating a serious problem.

To solve this, Rzepecki set out to develop new algorithms and AI friendly approaches. He also chose not to adopt legacy tools that had long been used in the industry, as they can be incompatible with machine learning and AI. Instead, he rebuilt everything from scratch.

However, designing from scratch has its challenges – for example, at the beginning the team tried to design a general-purpose storage solution for our complex data, but the decision back-fired.“We realized the system was too complex, and development was taking far too long.”

The reason they initially assumed a general-purpose system was simple. “We didn’t yet know how we would work with customers or what capabilities we would ultimately need to provide,” remarks Rzepecki. From this experience, their team learned an important lesson: “If you try to design software that will remain useful for many years into the future, you will often miss the mark. It’s better to develop something as small and simple as possible, and that is clearly aligned with its purpose, and then upgrade it as you go.”

There were other challenges as well. Most of his customers were major companies in the automotive industry, while Monumo was still just a small startup with little name recognition. Even when the company emphasized how much their new technology could help with the development of electric motors and EV powertrains, the response was dismissive. They simply weren’t taken seriously. From this experience, they learned the need to overcome the challenge of building credibility. "Developing the technology itself is only one part of the battle. You need to invest a lot of time in building the right data and solid examples, and make steady efforts to build trust with your customers.”

For engineers and young people unnerved by the rapid pace of AI technology worldwide, Rzepecki offers the following words of wisdom:

“We’re living in a time when the speed of engineering advancement has never been faster, and AI is one of the forces accelerating that momentum. All engineers, not just newcomers, should embrace AI and other new technologies without fear and learn how to use them effectively.”

“There’s another important point: take a holistic view of science and engineering. In my experience, the best ideas come from combining knowledge across different fields of science and engineering. So, especially while you’re young, immerse yourself in as many different areas of technology and knowledge as you can. And, as you master new technologies like software development, programming, and AI, enjoy this exciting era.”