HORIBA MIRA and Monolith enhance battery testing through AI

The partnership will provide a value-add technical offer for existing HORIBA MIRA and Monolith customers, as well as an attractive option for other OEM vehicle manufacturers and Tier 1 battery suppliers looking to enhance their development process.

The agreement gives Monolith access to HORIBA MIRA’s in-house R&D battery test data to train and enhance its Anomaly Detector (AD) and Next Test Recommender (NTR) algorithms and demonstrate how the technology works at scale.

At the same time, HORIBA MIRA’s advanced cloud-based data driven solutions will integrate Monolith’s tools to further advance its current product offerings. Its well-proven data driven digital twins, calibration optimisers, and global real-world scenario generators provide an eco-system for efficient virtual development and testing, reducing the need for expensive prototype vehicles and time required to develop optimised calibrations for batteries and other powertrains.

The combined offer will provide a complete system level optimisation toolchain, accelerating the development of sustainable transport solutions through data-driven insights.

Guy Foulger, Engineering and Technology Director, HORIBA MIRA, added: “As global automotive companies move towards a stronger focus on virtual development, partnerships which enhance our physical and virtual engineering capability are key to supporting customers with the robust tools they need.

Working with Monolith, the machine-learning platform for engineering, HORIBA MIRA will bring almost 80 years of automotive engineering and test experience to  enhance the development of sustainable transport solutions, leveraging the power of machine learning, AI and high-fidelity data-driven insights.”

Monolith is already democratising AI for engineering with its bespoke SaaS platform that uses no-code, machine-learning software, giving domain experts the power to leverage existing, valuable testing datasets for their product development. The platform analyses and learns from this information, using it to generate accurate, reliable predictions that enable engineering teams to reduce costly, time-intensive prototype testing programmes.

Integrating highly effective innovations such as a ‘Next Test Recommender’ tool and the industry’s first AI-powered ‘Anomaly Detector’ functionality, Monolith provides engineers with intelligent solutions to develop higher-quality products in half the time.