Mike Kenhard joined IAV Automotive Engineering as president in 2019, bringing a diverse career in systems engineering and “all sides of engines and engine controls” from his previous experience at AVL, Denso, Cosworth Technology and Ford. The U.K. native sees his new role leading the Germany-based company’s U.S. operation as “the most exciting opportunity yet.” Kenhard (below), who is a member of SAE’s strategic North American International Powertrain committee, shared his thoughts recently with Editor Lindsay Brooke at IAV’s Plymouth, Michigan, headquarters. Highlights of that interview follow.
What are IAV’s North American customers telling you they need through 2025?
There is a lot of need for e-axles, such as P4 rear-axle electric drive units. There is a lot of diversity in solutions in this area, as the industry has not yet converged on a set of architectures. We’re working with the OEMs but more so with Tier 1s who are getting into the e-axle arena. Some of them have good axle and gear experience but need, at a systems level, the integration of the electrical hardware, software and electronics. With our deep expertise as a software company, this is where IAV can provide value.
A P4 e-axle has a significant software overlay with a lot of integration and calibration.
Right. Many start-ups, for example, can take an e-motor, connect it mechanically to an axle, throw an inverter on it, and it works. That’s fine—but putting it in the hands of the public is a whole different matter. There are AUTOSAR standards and functional safety aspects to consider. The software build process must meet safety standards. These areas are where we can help those companies deliver a quality product.
To what extent is IAV investing in artificial intelligence?
To an increasing extent. The theme of our annual conference earlier this year was AI. It was about how we can apply AI to everything we do as a business. In some corners of the industry AI is thought of as being mainly for helping to make decisions in autonomous driving. But we’re applying it everywhere including to improve our program management.
What about using AI in testing?
Yes, to look for anomalies in test data. If you train the AI models around what is ‘good’ data, then throw it out to all the data, the AI will start looking for patterns and potential concerns. With a traditional linear algorithm you’d have to code every single piece. With AI, you’re training it to look for potential issues with the data and also within the test environment. Perhaps AI can help us ‘see’ that a bearing on a dyno is going bad, a situation that could affect the quality of data from that test cell. You still need to apply engineering excellence to dig into the detail. But this is one example of how, through creative thinking, we can ensure data quality by adding ‘intelligence’ to the process.
How engaged is IAV with the tech start-up community?
We are actively engaged. The life cycle of a start-up begins with great ideas. With that, they get the initial round of funding to proceed in developing the ideas. Once that happens, they fall into different categories. One is trying to do everything, which is a struggle as the cash burns and the process gets more drawn out than they imagined. Others take on only what they do well; they get the experts for the things outside their competencies.
That’s where we come in. Let’s say a company needs to get an e-drive into a demo vehicle. We put together a system, sourcing components and battery packs if needed, but it’s on a start-up scale. It’s not the full software process and full validation. We’re a flexible team and can move fast. Big companies, by comparison, struggle with that.Continue reading »