EV Battery Intelligence Platform
This is not just a battery fire prevention system.
This platform provides end-to-end battery lifecycle intelligence including diagnostics, grading, identity, repurposing, and thermal reconfiguration for second-life EV battery systems.
EV.ENGINEER™
Sudarshana Karkala
Co-Founder, Principal Architect | Thasmai Infotech Private Limited
End-to-End Battery Intelligence Workflow
The complete engineering lifecycle — from battery intake through diagnostics, grading, identity, repack, and deployment.
Battery Intake
Receive retired EV battery packs; log origin, make, model, age, and prior usage history.
Registration & Identification
Assign internal tracking ID. Capture pack serial, BMS firmware version, and physical condition.
Safety Inspection
Visual check for swelling, leakage, connector damage. HV isolation pre-test before any electrical contact.
Pack-Level Diagnostics
BMS communication, OCV/CCV measurement, insulation resistance, fault-code extraction, and pack-level capacity estimation.
⚑ Decision Gate 1 — Reuse / Disassemble / Scrap
✓ SOH > 80%: direct reuse → Validation → Deployment (shortcut path). ⚠ Degraded but viable: disassemble → Module testing. ✕ Unsafe / failed isolation: exit → Material recovery & scrap.
Module-Level Testing
Capacity measurement, inter-cell voltage imbalance, DC internal resistance, and thermal behaviour under load.
⚑ Decision Gate 2 — Repair / Proceed to Cells
✓ Minor imbalance: repair module → Re-test. ⚠ Degraded clusters: disassemble → Cell-level testing. ✕ Failed modules: exit → Scrap / material recovery.
Cell-Level Testing
Precision cycling: measured capacity, AC internal resistance at 1 kHz, self-discharge rate over 72 h, thermal rise under 1C load.
Cell Grading
Deterministic scoring (Grade A/B/C/D) based on capacity, IR, thermal stability, and safety risk. No subjective assessment.
⚑ Decision Gate 3 — Use / Reject
✓ Grade A & B: proceed → Cell matching & binning. ⚠ Grade C: limited use → Low-load applications only. ✕ Grade D: exit → Recycling pipeline.
Digital Identity Assignment
QR-based encrypted ID generated, printed as tamper-evident label, and linked to cloud digital twin with full test history.
Cell Matching & Binning
Algorithm groups cells by capacity band, IR range, and thermal profile for optimal electrical balance in new packs.
Repack Design
Mechanical and electrical design of second-life pack: series/parallel configuration, BMS integration, enclosure engineering.
Thermal Reconfiguration
Airflow corridors, heat sinks, cell spacing, and propagation barriers designed for target deployment environment.
Validation Testing
End-of-line charge/discharge cycling, safety interlock verification, BMS communication validation, and thermal stress test.
Second-Life Deployment
Certified pack deployed for stationary storage, rural electrification, telecom backup, or EV auxiliary systems.
Pack Gate
Post-diagnostics triage determines if the pack can be reused directly, requires disassembly for modular salvage, or must be scrapped for materials.
Module Gate
Evaluation of module health determines if specific sub-modules require repair or if the system can proceed to granular cell extraction.
Cell Gate
Final grading filters every cell; only those meeting Grade A/B thresholds proceed to the matching and repack design phase.
System Architecture Overview
Clear boundary definition across hardware, software, and platform layers to ensure development alignment.
Hardware Layer
- Sensors: Voltage, current, temperature probes (±0.1% accuracy)
- Test Benches: Pack tester (800V), module bench (60V/100A), cell cycler (5V/10A)
- Safety Systems: E-stop, isolation monitors, fire suppression, HV disconnect
- Edge Controllers: MCU/PLC for real-time data acquisition
Software Layer
- Data Acquisition: Real-time polling from hardware controllers & BMS
- Analytics Engine: SOH/SOC estimation, anomaly detection, health scoring
- Grading Logic: Deterministic A/B/C/D classification based on measured data
- Test Sequencing: Automated charge/discharge profiles & safety interlocks
Platform Layer
- Identity: Encrypted digital twin with QR/NFC physical labels per cell and pack
- Traceability: Full genealogy from OEM origin → disassembly → repack → deployment
- Lifecycle Tracking: Every test, grade, owner transfer, and event logged immutably
- Dashboard: Fleet analytics, predictive health modeling, operator alerts
3-Level Diagnostic Architecture
Battery failures originate at cell level and propagate upward. Our diagnostics resolve at every layer.
Pack Level
Baseline qualification through BMS communication, isolation testing, and fault history extraction.
- Key Metrics
- Insulation Resistance, OCV/CCV Delta, BMS Error Logs, Total Energy Throughput
- Sensors
- HV voltage/current transducers, isolation monitor, CAN/BMS interface
Module Level
Intermediate health mapping focusing on cluster imbalance and DC internal resistance characterization.
- Key Metrics
- Capacity Spread, Inter-cell Voltage Delta, Thermal Rise, DCIR
- Sensors
- Multi-channel voltage sense, precision current shunt, K-type thermocouples
Cell Level
Granular characterization using high-precision cyclers for final grading and matching.
- Key Metrics
- Measured Capacity (Ah), ACIR @ 1 kHz, Self-discharge Slope, Thermal Rise Factor
- Sensors
- 5V/10A precision cycler channels, EIS module, NTC thermal probes
⚠️ Battery failures originate at the cell level — micro-short circuits, lithium plating, SEI growth — and propagate upward through modules to the full pack. Detection must resolve at every layer.
Battery Diagnostic Hardware Platform
Real EV battery systems require continuous sensing and protection through hardware and BMS integration.
Physical Infrastructure
- Pack Test Bench: 800V-rated isolation tester, HV discharge fixture, BMS/CAN interface harness.
- Module Tester: 60V/100A precision load bench with per-cell voltage tapping.
- Cell Cycler: 5V/10A multi-channel automated racks (32–128 channels).
- Sensor Array: High-resolution voltage, current, and thermal probes (±0.1% accuracy).
- Safety System: Emergency disconnect, fire suppression mesh, isolation monitoring, E-stop.
- Label Printer: Industrial QR / NFC tag printer for encrypted identity stickers.
System Data Flow
Software System Architecture
Modern EV safety systems rely on continuous monitoring, anomaly detection, and predictive analytics to prevent thermal failures.
Dashboard & Reporting
Visual analytics, fleet reports, predictive health modeling, and operator alerts.
Identity & Traceability Engine
Cryptographic ID generation, genealogy tracking, and audit-ready lifecycle records.
Grading & Matching Logic
Deterministic scoring algorithms and cell-matching heuristics for optimal binning.
Analytics Core (SOH, SOC, IR, Temp)
Signal processing and multi-parameter health estimation with anomaly detection.
Test Execution Engine
Automated test sequencing, charge/discharge profile management, and safety interlocks.
Data Acquisition Layer
Real-time polling from hardware controllers, BMS interfaces, and sensor arrays.
Device Interface Layer
Hardware abstraction for cyclers, load banks, isolation testers, and label printers.
Deterministic Grading System
Multi-parameter qualification based on measured capacity, internal resistance, thermal stability, and safety risk.
Encrypted Battery Digital Identity
The foundation for the Battery Pack Aadhaar ecosystem — every cell gets a unique, tamper-proof identity.
Identity Framework
- QR-based Identity: Tamper-evident physical labels with encoded cell/pack metadata.
- Encrypted Token: AES-256 crypto-link between physical label and cloud digital twin.
- Backend Mapping: Full genealogy from origin OEM pack → disassembly → new repack configuration.
- Genealogy Tracking: Every test, grade, owner transfer, and deployment event logged immutably.
Identity Lifecycle
Thermal Reconfiguration for Second-Life Packs
Redesigned thermal management is essential to prevent heat propagation and battery failure in repacked configurations.
Cooling Strategy
Active forced-air corridors and passive heat sinks integrated into the pack housing. Dual-mode operation: fan-assisted during charge, passive during standby.
Airflow & Cell Spacing
Directed airflow channels between cell clusters. Mica/ceramic propagation barriers with optimized inter-cell pitch spacing to limit thermal runaway propagation.
Heat Dissipation
Structural aluminium heat sinks and thermally conductive gap fillers to manage peak charge/discharge thermal events without active liquid cooling.
Core Thermal Design Principles
- Airflow / Cooling: Active forced-air corridors with dual-mode operation (fan-assisted during charge, passive during standby)
- Cell Spacing: Optimized inter-cell pitch with mica/ceramic propagation barriers to limit thermal runaway chain reaction
- Heat Dissipation: Structural aluminium heat sinks and thermally conductive gap fillers for peak thermal events
- Safety Margin: Designed for 45 °C+ ambient (Indian conditions) — no dependence on external HVAC; passive safety sustains operation in non-climate-controlled environments
Product Roadmap
From MVP diagnostics platform to national-scale Battery Pack Aadhaar integration.
Diagnostics Platform
- Pack/Module/Cell test benches
- Data acquisition pipeline
- Baseline SOH estimation
Grading & Identity
- Deterministic grading engine
- QR/NFC identity system
- Cloud digital twin
Repack System
- Cell matching algorithms
- Mechanical pack design
- BMS integration framework
Thermal Optimization
- Airflow simulation
- Propagation barrier design
- Rural environment validation
Battery Pack Aadhaar Registry Integration
National-scale traceability, circular lifecycle ecosystem, and regulatory compliance framework connecting every second-life battery cell to a unified digital identity registry.
Engineering the Future of Battery Intelligence
A real, buildable infrastructure for second-life battery diagnostics, grading, identity, and safe deployment.