Evident Battery uses mechanical vibration analysis and deep learning to detect hidden faults across the entire electric vehicle battery pack. The platform extracts unique vibration signatures to identify mechanical and integration failures often missed by standard methods. This process delivers clear, actionable diagnostic reports quickly, supporting quality assurance for manufacturers, accurate valuation for dealerships, and faster claims processing for insurance providers.
Funding
$3M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Evaluating the health and lifespan of electric vehicle (EV) batteries typically requires destructive testing or time-consuming manual inspections. Existing post-sale inspection technologies often focus solely on battery cell measurement, overlooking critical aspects such as the thermal system, insulation, internal structure, and enclosure. This makes it difficult to quickly and accurately assess battery condition, predict remaining lifespan, and determine financial value.
Solution
EVident Battery offers automated, non-destructive inspection systems for EV battery packs, providing a comprehensive assessment of battery health, life expectancy, and financial value. The system employs a robotic mobility system equipped with various sensors to perform a detailed scan of the battery pack. Data signatures are correlated with known failure modes, and sophisticated machine learning algorithms are used to enhance the assessment. The result is a detailed report on the battery's health, an estimated remaining lifespan, and its financial valuation, delivered in minutes.
Target Audience
The primary target audience includes EV manufacturers, service facilities, dealerships, insurance companies, car fleet management companies, and individual EV owners who need reliable battery inspections and evaluations.
Features
- Comprehensive, non-intrusive inspection and imaging of EV battery packs
- Advanced robotic mobility system equipped with multiple sensors
- Analysis of the thermal system, insulation, internal structure, and battery pack enclosure
- Correlation of data signatures with known failure modes
- Machine learning algorithms for enhanced assessment of battery condition
- Detailed reports on battery health, estimated remaining lifespan, and financial valuation
- Fast inspection times, with results available in approximately two minutes