According to Monolith, an artificial intelligence (AI) software provider, its study – commissioned from Forrester Consulting and titled AI for EV Battery Validation - reveals that nearly two thirds of automotive leaders expect the potential impact of AI to be extremely or very significant with over half indicating that Engineering AI (EngAI) will be crucial to staying competitive in electric-vehicle (EV) battery development.
The study, which surveyed 165 senior decision-makers in automotive engineering in North America and major European automotive markets, explored their views on the application of EngAI in the development of EV batteries and revealed 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.
According to Dr. Richard Ahlfeld, CEO and Founder of Monolith, “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’s what automotive leaders are starting to understand.
“Of course, there’s 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.”
The study found that 64% of automotive engineering leaders stressed the requirement to reduce the time and effort spent on EV battery validation and in the same vein, two out of three believe it’s imperative to reduce dependency on physical tests, while still ensuring compliance with safety and quality standards.
The report found that 66% of senior decision-makers said that it was imperative to reduce reliance on physical test while still ensuring compliance with safety and standards, and 62% said that their current virtual validation tools, including physical simulation, did not fully ensure that battery designs met all validation criteria.
The influence that EngAI is increasingly having in the automotive industry has driven more focus on the technology among automotive engineering leaders. While 44% of respondents express serious concern about the potential effect that the technology could have on their business’ staff-count, over half (58%) have declared AI to be critical in ensuring they stay competitive in EV battery development.
The automotive industry has seen unpredictable levels of demand for EVs in recent times, compounded by broader macro-economic circumstances. Commercial pressures felt in these conditions have led senior engineering decision-makers to seek smarter solutions for reducing costs and development time – and EngAI is expected to make waves in this respect.
Respondents expect EngAI to cut years, quarters or months in development cycles – including in cell characterisation testing (61%), module and pack testing (56%) regulatory testing (53%) and charging optimisation testing (48%).
Meanwhile, they anticipate AI will help them achieve significant cost savings in terms of ageing and lifetime battery testing (37%), repeating tests due to failures (39%), thermal runaway testing (36%), and regulatory testing (32%).
