EV Battery Pack Digital Twin for Real-Time Charge Profile Optimization
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Solution Overview
Problem
Current battery management systems for electric vehicles face challenges in optimizing battery pack operation due to the need for real-time integration of mathematical models and historical data to predict state of charge, state of health, and thermal profiles, which is complex and often done offline.
Innovation Solution
A system comprising an input/output interface, hardware processors, and memory that preprocesses data from the battery management system to generate thermal, SOH, and SOC models, as well as a cell balancing model, to optimize current profiles for charging and discharging based on constraints such as temperature rise and SOH, using an objective function.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If mathematical models and simulation tools are used independently for prediction of SOH, SOC, then prediction capability is provided, but integration complexity and computational burden increase
Solution Approach 1:
The patent combines multiple independent mathematical models (thermal model, SOH model, SOC model, SEI layer model, cell balancing model) into a unified integrated framework that processes battery data collectively. This merging approach maintains the predictive capabilities of each individual model while reducing overall system complexity through shared data preprocessing and coordinated optimization, directly resolving the contradiction between prediction reliability and integration complexity.
2Productivity
If multiple models are coupled in real-time, then optimization capability is enhanced, but computational complexity and processing requirements increase
Solution Approach 1:
The patent segments the complex computational task into distinct modular models (thermal model for temperature prediction, SOH model for health assessment, SOC model for charge state, SEI layer model for degradation tracking, cell balancing model for equalization). Each segment processes specific aspects of battery operation independently but contributes to the overall optimization, enabling real-time operation while managing computational complexity through division of labor.
Solution Approach 2:
The system dynamically adjusts operational parameters (charging current, discharging current, cooling flow rate) based on real-time predictions from the coupled models. By changing these parameters adaptively according to the integrated model outputs, the system achieves enhanced optimization capability while the computational complexity is managed through focused parameter adjustment rather than complete system reconfiguration.
3Measurement precision
If comprehensive data preprocessing and feature extraction are performed, then model accuracy improves, but processing time and computational resources increase
Solution Approach 1:
The patent performs data preprocessing and feature extraction as preliminary actions before feeding data into the various models. By preparing the data in advance (normalization, feature selection, noise filtering), the system improves model accuracy while the preprocessing results can be reused across multiple models, reducing redundant processing and overall computation time.
Data Source
AI summary
The efficient operation of an electric vehicle depends greatly on proper functioning of a battery pack in the electric vehicle. A system and method for optimizing the operation of the battery pack in an electric vehicle is provided. The system comprises a digital twin for a battery pack in an electric vehicle. The system determines the state of charge, state of health and temperature distribution in the battery pack using various models. This information can be used to predict optimal charge and discharge profiles of the battery pack for given load conditions, as well as remaining useful life of the battery. The digital twin would require inputs such as battery temperatures from the sensors, coolant flow rates, coolant temperature, ambient temperature, load on the vehicle, current and voltages from the pack and battery characteristics from the manufacturer.