Battery Physical Parametrization with ECM and P2D Models
Powered by APEX AI OS — Physics
While developing highly accurate Equivalent Circuit Models (ECM) and Pseudo 2-Dimensional (P2D) models is critical for advanced battery design, manual parameterization remains a massive engineering bottleneck. Testing teams currently spend weeks painstakingly analyzing complex charge/discharge data and manually curve-fitting parameters across varying temperatures, SOCs, and C-rates — a process that introduces human error and severely delays time-to-market. Automated parameterization with the APEX Physics App eliminates this friction by rapidly ingesting cell data to speed up the process to build fully validated, ready-to-use models. By automating the parameter optimization process and model export, engineering teams can drastically accelerate battery development, guarantee robust performance across all operational windows, and confidently rely on comprehensive validation reports.
HOW IT WORKS
1. AI model support
Trained on 4,000+ real-life cycling tests and>10M material configurations, effectively learnswhat models and parameters to optimize bothECM and P2D modes based on test data.
2. Optimization
Minimal optimization adaptation to your specificcell chemistries and test protocols. Develop acustomer specific high-accuracy model to buildIP and your battery intelligence. Optimization isrun on cloud infrastructure to ensure highconvergence speed.
3. Simulation
Simulate any test conditions by using batterymeasurement templates or an LLM promptfunctionality that generates operating conditionsand profiles for simulation automatically.
USE CASES & BENEFITS
Rapid Cell Material Screening & Optimization
Automatically extracts parameters from test data to help evaluate how physicalchanges — like electrode thickness, porosity, or active material composition —impact cell performance across varying operating conditions.
Cross-context cell models, from BMS to power validation
Automatically optimize ECM models to match temperature, C-rate, SOC and SOHdependent operation condition matrices. Ready to use in BMS or thermal highpower validation during fast charge.
Advanced Aging and Degradation Analysis
Isolates specific degradation mechanisms early in the testing phase, allowingengineers to pinpoint exactly how and why a cell is failing under specific thermalor SOC conditions.
Cloud computing for parallelizable optimization
Benefit from Sphere energies cooperation with german based cloud providerStackIT, to speed up your calibration process.
ENGAGEMENT & PRICING
1. Integrate into your Data pipeline
Automated parametrization model tested with your data.Flexible configuration of experimental fitting with eitherECM or P2D models.
2. Integration
Customization of automated parametrization accordingto your business and expected insight generation. All IPremains with you, run on your premises.
3. Deployment & License
Private cloud or on-premises within your infrastructure.Possible integration and run with other Sphere’s offering,e.g.: testing, data management, etc.
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