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A Groundbreaking Presentation on the Combined Electrochemical and Machine Learning Model for Predictive Battery Intelligence
Last week, ITEC+ 2022 brought top academics and leaders from the electric vehicle, battery technology, sustainability, and aerospace industries together to share state of the art research and technology. In his tutorial presentation at the ITEC+2022 Symposium, Electra Vehicles CEO and Co-Founder, Fabrizio Martini, presented on “AI-Based Battery Management Techniques: Advanced Adaptive Cell Modeling” to a full, interactive audience.
Martini shared details on the Adaptive Battery Digital Twin, a Cloud-based battery model that continuously learns through AI/ML techniques to provide an accurate picture of the EV battery over time. This innovation represents a pivotal step forward in vehicle electrification to increase EV reliability and, ultimately, EV adoption.
Taking a digital twin approach to battery modeling is strongly supported by the scientific community. The Adaptive Battery Digital Twin revolutionizes battery management by uniquely combining physics-based electrochemical and Machine Learning models. The electrochemical model of the individual battery chemistry creates a physical representation of battery degradation over time.
Concurrently, the Machine Learning architecture intakes real time data from the BMS, driver behavior, vehicle use cases, and environmental factors. This information is critical for the model to continuously learn from ongoing battery usage. The hybrid approach of the Adaptive Battery Digital Twin singularly takes data science and electrochemical analysis into account to provide accurate and essential predictive knowledge.
This technology is particularly important in this moment, when 57% of Americans worry their EV will not provide sufficient range. Their concern is warranted: in fact, 54% of all vehicle breakdowns are related to EV batteries. As OEMs shift to EV production and climate advocates push to electrify transport, range and reliability are crucial.
EV recalls and thermal events often permeate the news cycle – notably the 2021 Chevy Bolt and Hyundai Kona recalls. In both events, the manufacturers provided reactionary software updates to mitigate future risk, but did not have the tools in place to predict and mitigate the failures ahead of time.
By contrast, Electra’s EVE-Ai™ 360 Adaptive Controls proactively reveals and prevents future battery failures at the OEM, fleet, and user levels. Electra optimizes the Adaptive Battery Digital Twin to dynamically implement the most appropriate ML architecture based on the vehicle’s profile.
Presenting Electra's groundbreaking technology at ITEC+ 2022 marks a milestone for the fast-growing startup in connecting with academic and industry experts alike across the battery and EV fields. With the goal of accelerating widespread electrification, Electra implements the Adaptive Battery Digital Twin as the core of active, adaptive, and Cloud-connected battery management controls and predictive fleet analytics.
Want to learn more about Electra’s EVE-Ai™ 360 Adaptive Controls and Fleet Analytics? Follow us on LinkedIn and Twitter to to meet Fabrizio at our next event and to stay up to date on Electra’s latest news, or reach out here to schedule a meeting.