Electra Vehicles’ AI Software Demonstrates 2x Accuracy of EV Driving Range Estimates

Electra Vehicles, Inc., a leading provider of predictive battery management
and battery design software, today announced the results of a demonstration
to showcase accuracy improvements to electric vehicle driving range
estimations. Electra’s core technology – EVE-AiT Adaptive Cell Modeling
System – outperformed the industry standard for estimating battery charge,
resulting in 2x reduction in estimation error.

Electra partnered with a semiconductor provider to construct a battery pack
that was capable of delivering real-time battery cell data from the pack to
Electra’s cloud-based EVE-AiT software through a battery management system
and IoT gateway hardware. Using this setup, Electra showcased that its
integrated software solution could retrain the battery management system
using artificial intelligence and machine learning to predict a battery’s
state-of-charge more accurately than the industry standard method, known as
Extended Kalman Filtering (EKF).

“By showcasing significant improvements in predicting a battery’s
state-of-charge, Electra has demonstrated how using artificial intelligence
in battery management can translate to longer lasting and better performing
batteries,” said Fabrizio Martini, Electra CEO and Co-Founder. “With
Electra’s EVE-AiT software, the vehicle’s battery management system is
constantly retrained to showcase the most accurate battery metrics,
alleviating range anxiety and battery warranty concerns for EV customers.”

The test battery pack was repeatedly charged and discharged over a 12-week
period in order to quickly age the pack to roughly half of its warranty for
electric vehicle usage. Throughout the testing, Electra compared three sets
of results – estimates from Electra’s EVE-AiT Adaptive Cell Modeling System,
estimates from the industry standard EKF and the reference values from an
electrochemical reference data set.

The results showed that Electra’s solution better predicted the battery’s
state of charge at the beginning of life, but more importantly, as the
battery reached half-life, which is where Electra’s accuracy improved
significantly over EKF.

To learn more about the demonstration methodology, please watch an overview
via Electra’s Vimeo. To learn more about the demonstration results, please
download the case study here or reach out to an Electra sales representative
via sales@electravehicles.com

About Electra Vehicles, Inc.

Electra Vehicles is on a mission to maximize the full potential of battery
power to enable electric mobility to take us further.

Electra is a leading provider of predictive battery management and battery
design software that combines adaptive electrochemical battery modeling with
advanced artificial intelligence and machine learning algorithms to more
accurately predict battery performance, health and failures. Electra’s
software solutions are both cloud-based and ‘hybrid’ – embedded in the
battery management system (BMS) with cloud connectivity – and enable battery
developers, battery integrators and fleet managers the ability to more
accurately estimate battery state-of-charge (SoC), state-of-health (SoH),
remaining useful life (RUL) and fault risk to improve the lifetime and
reliability of batteries.

Learn more at: https://www.electravehicles.com