Battery Performance Management

Monitoring the health and performance of batteries, such as electric vehicle batteries, requires appropriate monitoring and analytics. This can be achieved through a battery digital twin, a virtual representation that mirrors the physical characteristics, behavior, and performance of a battery while the battery is in use. Battery Performance Management solutions on AWS provide insights into battery performance through digital twin, machine learning, and analytics services to monitor battery condition, extend EV lifespan, and predict issues like lithium plating or thermal runaway.

Partner Solutions
Guidance

Partner Solutions

Software, SaaS, or managed services from AWS Partners

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  • Voltaiq Battery Quality Analytics

    Voltaiq helps battery manufacturers identify issues faster, decreasing scrap rate and reducing manufacturing ramp-up time. With Voltaiq, battery engineers are alerted to problems within the first hours of formation to find and fix upstream issues fast. Understand the full extent of an issue in just a few clicks without any manual data collection or processing and identify which upstream processes and materials led to the defects. Engineers can quickly generate reports and dashboards to share findings for faster resolution without having to manually gather and structure data. Voltaiq boasts the largest install base in the battery industry with the most third-party integrations and partnerships for seamless system integration. The de facto standard in battery quality analytics, Voltaiq proudly offers dedicated consulting services and hands-on customer support. Voltaiq is trusted by industry leaders including Freyr, Amazon, Mercedes-Benz, Albemarle, and Lyten.
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Guidance

Prescriptive architectural diagrams, sample code, and technical content

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  • Battery Digital Twin on AWS

    This Guidance shows how to create a battery digital twin, a virtual representation of a physical electric vehicle battery or battery energy storage system (BESS), and overlay real-time data such as voltage, current, and temperature.

  • Electric Vehicle Battery Health Prediction on AWS

    This Guidance demonstrates how to use historical battery health data with artificial intelligence and machine learning (AI/ML) algorithms to improve the accuracy of battery State of Health (SoH) and Remaining Useful Life (RUL) estimations.

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