Software algorithm in Simulink Stateflow for charge levelling between multiple battery packs

The aim was to determine which secondary use battery section configuration would be the most attractive and optimal for an automotive power battery

Objective

The key objective of the study was comparison of the options and benefits of utilizing air cooled power batteries in different sectional configurations with SOC balancing

Our Approach

Market Assessment

Determined Battery architecture (series/parallel combination of battery packs) that shall satisfy the required conditions

Capacity Building

Determined capacity of the battery pack decommissioned from the vehicle (SoH correction for aged pack capacity)

BMS Architecture

Developed a Battery Management System (BMS) based on the architecture of the battery pack to balance multiple packs based on individual SOC and Capacity using passive methods

Validation and Implementation

Validated Battery bank through simulation over pre-defined real-world load-cycles

Outcome

Analysis of Parallel/ Series eAssist battery architecture and parallel balancing
Comparison of current baseline vs other solutions based on Functionality, Cost, Reliability, Parasitic Load Consumption, Maximize utilization of existing hardware (analysis with and without Parallel Balancing Units)
Comparison of the currently planned demonstration project execution with current eAssist battery modules to the eventually planned next generation systems.
Successful adaptation and application of mixed capacity section-based Battery State Estimator algorithm to Secondary Use system

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