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Test equipment

Nissan harnesses AI to speed up physical vehicle tests

Zahra AwanBy Zahra AwanNovember 3, 20253 Mins Read
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A test engineer sits in the driver seat of a Nissan test vehicle

Nissan and Monolith have announced a three-year extension to their strategic partnership, using artificial intelligence (AI) to transform the vehicle development process and reduce the use of physical tests.

Initially used to validate testing on the latest Nissan Leaf electric vehicle built in Sunderland, Monolith’s AI technology will now be applied to a wider range of tests for Nissan’s upcoming European models.

Engineers at Nissan Technical Centre Europe in the UK will harness historical test data and use Monolith’s AI technology to predict the results of physical tests. This will reduce the reliance on physical prototypes, streamline the development process and enable engineers to focus on hands-on problem solving and decision-making, Nissan said.

The decision to extend the partnership follows a previous collaboration between Nissan and Monolith using AI to test the performance of bolt joints in vehicle chassis. The AI technology recommended the optimal torque range for bolts to be tightened and reliably prioritized additional tests for engineers to carry out. This resulted in an overall 17% reduction in physical testing compared to the non-AI process. Applying the same approach across the development of all Nissan’s European vehicle range could cut testing time by half.

Commenting on the partnership, Emma Deutsch, director of customer-oriented engineering and test operations, Nissan Technical Centre Europe, said, “By integrating Monolith’s advanced AI-driven engineering software and decades of testing data, we’re able to simulate and validate vehicle performance with remarkable precision.

The partnership contributes to Nissan’s global recovery plan, RE:Nissan, which includes a focus on bringing products to customers more quickly by reducing vehicle development time and working with partners to drive innovation and operational efficiency.

Deutsch said, “Their machine learning models, trained on a combination of historical test data and digital simulations, allow us to reduce reliance on physical prototypes – cutting development time and resource use significantly. This approach not only accelerates our time to market but also supports our commitment to innovation and sustainability. As we look to the future, AI will play an increasingly central role in how we design, test and deliver the next generation of vehicles to our customers sooner.”

Dr Richard Ahlfeld, CEO and founder of Monolith, said, “Our mission is to empower engineers with AI tools that unlock smarter, faster product development. The results of our work with Nissan demonstrate how machine learning can drive efficiency and innovation in automotive engineering. We’re thrilled to continue this journey together.”

In related news, Foretellix integrates Foretify physical AI toolchain with Nvidia Drive AV platform

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Previous ArticleVector launches cube:tap interface for LTE-V2X
Zahra Awan

Zahra brings her background in reporting on the heavy manufacturing industry together with her passion for automotive as web editor at UKi Media & Events. She is keen to connect with people across the sector who share her enthusiasm for automotive innovation.

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