Core Technology & Roadmap
Reimagining battery management systems by simultaneously tackling hardware sensor reduction and algorithmic complexity reduction.
The Problem & Our Solution
The Problem
- close Relying on onboard voltage sensors for every cell decreases BMS reliability when sensors fail and increases computational load.
- close Existing literature typically reduces either hardware complexity (fewer sensors) or software complexity (simpler code), but rarely addresses both together.
Our Solution
- check Reimagines the entire battery pack as a single "average" model, performs state estimation over this average model, and then distributes this estimation to each single cell.
- check Focuses on both sensor reduction and algorithm complexity reduction, reducing software development/maintenance and increasing reliability when sensors fail.
Average Model & State Distribution
Our breakthrough method bypasses the requirement of measuring every single cell in real time.
Sensor Reduction
Reduces dependency on physical onboard voltage sensors, removing single points of failure across the battery pack.
Average Pack Modeling
Runs efficient state estimation algorithms across the pack-level average model, drastically lowering computational footprint.
Cell-Level Distribution
Mathematically distributes the average estimation to individual cells, retaining state accuracy while cutting complexity.
Technology Readiness Level (TRL) & Roadmap
Current readiness level and industrial prototyping milestones.
Current Phase
TRL 3: Lab-Scale Prototype
Working low-voltage prototype (~15V) with validated state estimation algorithms. Software enhancements underway over the next few months.
Next Milestone (1–2 Years)
TRL 4: Industrial Prototyping
Collaborating with industrial partners to prototype and demonstrate at industrial scale (~150V in EV battery packs), targeting a complete industrial prototype in 2–3 years.