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Survey’s Results: Optimism and Caution in AI Adoption for EV Battery Development

Monolith AI's EV battery AI adoption survey reveals industry optimism and caution in integrating artificial intelligence.

Maria Guerra, Senior Editor-Battery Technology

May 8, 2024

3 Min Read
Battery testing and AI
Monolith (engineering AI firm) commissioned Forrester to survey senior decision-makers in battery for opinions on AI.Chattrawutt/iStock / Getty Images Plus

Monolith AI's recent survey on the application of artificial intelligence (AI) in electric vehicle (EV) battery validation sheds light on the perceptions and expectations of senior decision-makers within the automotive industry. The survey, conducted by Forrester Consulting in 2024 and titled “AI for EV Battery Validation,” involved 165 participants from automotive engineering sectors in North America and major European markets, providing valuable insights into the evolving landscape of EV battery development.

One of the central themes of the survey is the growing recognition of the importance of AI, particularly engineering AI (EngAI), in driving innovation and competitiveness in the EV market. Over two-thirds of respondents expressed optimism about the potential impact of AI, with more than half identifying EngAI as crucial for staying competitive in EV battery development. This underscores a widespread acknowledgment of AI as a transformative force in addressing the complex challenges associated with battery testing and validation.

Richard Ahlfeld, CEO and Founder of Monolith stated, “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.”

Related:AI Tool Reduces Battery Testing by Up to 70%

AI testing concerns

However, amidst the enthusiasm for AI-driven solutions, questions arise regarding the safety and reliability implications of reducing physical testing in favor of AI-driven validation methods. Physical testing serves as a cornerstone of product validation, providing essential insights into factors such as durability and thermal management, to name a few. Reducing reliance on physical tests risks overlooking potential failure modes or performance limitations that may only become apparent under real-world conditions.

Ahlfeld continued, “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 survey findings highlight a cautious approach among industry leaders regarding reducing physical testing. While there is widespread recognition of the potential efficiencies offered by AI, concerns persist about the need to ensure the safety and reliability of EV batteries. Two-thirds of respondents expressed the importance of reducing dependency on physical tests while ensuring compliance with safety and quality standards, indicating a desire to strike a balance between innovation and risk mitigation.

Related:Enhancing EV Battery Performance with Advanced Inspection Solutions

Moreover, the survey underscores the need for a robust framework for data integrity, model validation, and algorithm transparency in AI-driven validation processes. Ensuring the accuracy and reliability of AI predictions requires comprehensive validation against empirical data and ongoing monitoring to detect and mitigate biases or errors. This highlights the importance of responsible and ethical AI deployment in ensuring the safety and reliability of EV batteries.

Monolith AI's survey provides valuable insights into the perceptions and expectations surrounding the integration of AI in EV battery development. While there is optimism about AI's potential efficiencies, concerns persist about the safety and reliability implications of reducing physical testing. By adopting a cautious and responsible approach, automotive companies can harness AI's transformative potential while ensuring the safety and reliability of EV batteries in an evolving landscape of battery development.

Editor's note: Monolith AI CEO Richard Ahlfeld will be a conference speaker at The Battery Show Europe in June.

About the Author(s)

Maria Guerra

Senior Editor-Battery Technology, Informa Markets Engineering

Battery Technology Senior Editor Maria L. Guerra is an electrical engineer with a background in Oil & Gas consulting and experience as a Power/Analog Editor for Electronic Design.  Maria graduated from NYU Tandon School of Engineering with a Master of Science in Electrical Engineering (MSEE). She combines her technical expertise with her knack for writing. 

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