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Jib arm Crane Swinging 3 ton capacity Powermaster, approx 4m high and 4m arm, with electric hoist.Pr
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AI seen as crucial to battery development

Posted on 22 May 2024. Edited: Colin Granger. Read 365 times.
AI seen as crucial to battery developmentLondon-based Monolith AI Ltd — an artificial intelligence (AI) software provider — has launched its newly commissioned Forrester Consulting 2024 study titled AI for EV Battery Validation. This reveals that nearly two-thirds of automotive leaders (165 senior decision-makers in automotive engineering in North America and major European automotive markets) expect the potential impact of AI to be extremely or very significant. Over half indicated that Engineering AI (EngAI) — a ‘sensible form of AI that learns from masses of engineering data to help test teams understand otherwise intractable problems’ — to be crucial to staying competitive in EV battery development’.

“In an industry increasingly dominated by balancing the seemingly conflicting goals of faster time to market and maintaining high product quality, the study reveals first-hand insights into the pressures that automotive engineering players are facing in the race to develop industry-leading vehicles, and where intelligent technologies such as AI can address these urgent challenges to accelerate innovation.”

Richard Ahlfeld, Monolith’s CEO and founder, said: “EV, and particularly battery development, is highly competitive; and with that comes a lot of pressure to move faster. Engineering AI can learn to solve problems much faster than any human, and that is what automotive leaders are starting to understand.

“Of course, there is uncertainty and misunderstanding around AI, but if you have to squeeze what previously took five years into three, engineers need to make the most of the new tools available to them. AI built specifically for engineering offers an intelligent, cost-effective solution for leaders in the automotive industry to gain a competitive edge, faster.”

Respondents to the study say they expect EngAI will significantly cut development times, including in cell characterisation testing (61%), module and pack testing (56%), regulatory testing (53%), and charging optimisation testing (48%). They also anticipate that AI will help them achieve cost savings from $10 million to over $100 million in ageing and lifetime battery testing (37%), repeating tests due to failures (39%), thermal runaway testing (36%), and regulatory testing (32%).