Electra Vehicles will return to CES 2026 in Las Vegas, January 6th to 8th (West Hall, Booth 7324) to demonstrate how artificial intelligence is being applied to battery monitoring, optimization, and management for electric vehicles (EVs) and related energy storage applications.
At CES, Electra will present its AI-based battery intelligence platform designed to improve battery performance, safety, and lifetime across electric mobility systems. The company’s technology applies predictive analytics and adaptive controls to battery cells and packs, enabling real-time insight into battery health, usage, and risk conditions.
Building on earlier vehicle demonstrations, Electra has transitioned its AI platform from pilot programs to scalable deployments supporting EVs and other electrified assets. The platform is designed to operate across different battery chemistries, pack designs, and operating environments, supporting vehicle-based and stationary energy storage use cases.
Electra’s battery intelligence platform is deployed across multiple regions, including North America, Europe, and Asia, and is used to support battery systems operating in varied duty cycles and environmental conditions.
Battery intelligence for EVs
Across EV fleets, operators face persistent challenges related to efficiency, degradation, safety risk, and total cost of ownership. These challenges are often compounded by limited predictive insight into battery behavior over time and across operating conditions.
In EV applications, many of these limitations stem from conventional battery management systems (BMS) that rely on static models and rule-based controls. As vehicle usage patterns, charging behaviors, and operating environments become more variable, BMS architectures increasingly require predictive and adaptive intelligence to manage battery performance and safety more effectively.
Electra’s approach applies AI-based modeling to battery data collected from cells, packs, and environmental sensors to enable predictive battery management. The platform is designed to support earlier detection of degradation and failure modes, more accurate estimation of state of charge and state of health, and adaptive optimization of charging and operating profiles.
The EVE-Ai platform
Electra’s EVE-Ai platform is built as a software-based intelligence layer for batteries, combining cloud analytics with embedded control capabilities. The platform is chemistry- and hardware-agnostic and is intended to integrate with existing battery management system architectures.
EVE-Ai consists of two primary components:
- EVE-Ai Battery Fleet Analytics (BFA): A cloud-based system for monitoring and analyzing large fleets of EV and stationary batteries. The platform provides predictive analytics, maintenance insights, and asset-level visibility to support operational planning and lifecycle management.
- EVE-Ai Adaptive Controls: An embedded intelligence layer that operates at the battery level, enabling real-time optimization of charging behavior, health management, and safety controls within the battery management system.
According to Electra, deployments of the EVE-Ai platform have demonstrated measurable improvements in battery utilization, operational uptime, and lifecycle extension through predictive analytics, early risk detection, and adaptive control strategies.
At CES 2026, Electra will demonstrate how AI-driven battery intelligence can be applied to EV and energy storage systems to improve performance, safety, and long-term asset value as electrification continues to scale.
Filed Under: Software, Technology News