Dynamic Balancing Target Switching for EV Battery Modules
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Solution Overview
Problem
Existing methods for balancing electrical energy storage modules in electric vehicles do not efficiently adapt to changing operating conditions, leading to suboptimal performance due to uneven state of charge distribution and varying battery cell characteristics.
Innovation Solution
A method and system that dynamically switch between different balancing target types based on present and future operating conditions, allowing for optimization of energy storage module performance by adjusting characteristics such as state of charge, open circuit voltage, charge power, and discharge power.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a fixed balancing target type is used for the energy storage module, then the balancing process is simple and stable, but the performance optimization is insufficient under varying operating conditions
Solution Approach 1:
The patent implements dynamic switching between different balancing target types (state of charge balancing, open circuit voltage balancing, charge power capability balancing, discharge power capability balancing) based on predicted future operating conditions. The system transitions from static to dynamic balancing strategy, adapting the balancing target type according to whether the vehicle will be used for commuting, long-distance travel, or stationary operations, thereby resolving the contradiction between balancing stability and performance optimization.
Solution Approach 2:
The system performs preliminary prediction of future operating conditions using historical data and route information before executing the balancing process. By predicting whether the vehicle will be used for commuting, long-distance travel, or stationary operations in advance, the system can proactively select the appropriate balancing target type, ensuring optimal performance when the predicted operating condition occurs.
2Productivity
If dynamic switching between balancing target types is implemented, then performance optimization is improved, but the system complexity increases
Solution Approach 1:
The patent segments the balancing control system into distinct modules: a prediction module that forecasts future operating conditions, a selection module that chooses the appropriate balancing target type, and execution modules for different balancing strategies (state of charge balancing, open circuit voltage balancing, charge power capability balancing, discharge power capability balancing). This modular segmentation manages system complexity by organizing the dynamic switching functionality into manageable, independent components.
Solution Approach 2:
The balancing control system is designed with multi-functionality, capable of performing multiple balancing target types (state of charge, open circuit voltage, charge power capability, discharge power capability) and multiple prediction models (commuting, long-distance travel, stationary operations) within a single integrated framework. This universal design allows the system to adapt to various operating conditions without requiring separate dedicated systems for each scenario.
3Ease of operation
If balancing is performed based on present operating condition only, then the response is immediate and simple, but the future performance optimization is limited
Solution Approach 1:
The system incorporates feedback mechanisms by continuously monitoring present operating conditions and comparing them with predicted future conditions. Historical operating data is fed back into the prediction model to improve future predictions, and the system adjusts the balancing target type selection based on this feedback loop, ensuring both immediate response capability and future-oriented optimization.
Solution Approach 2:
The system performs preliminary prediction of future operating conditions using historical data and route information before executing the balancing process. By predicting whether the vehicle will be used for commuting, long-distance travel, or stationary operations in advance, the system can proactively select the appropriate balancing target type, ensuring optimal performance when the predicted operating condition occurs.
Data Source
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AI summary
The invention relates to a method for balancing an electrical energy storage module (1) comprising a plurality of units (3) for an electric vehicle (5). The energy storage module (1) is operative according to a first balancing target type. A present operating condition of the energy storage module is determined (S402), and a future operating condition of the energy storage module is determined (S404). Further, there is selected (S406) a second balancing target type among a plurality of predetermined balancing targets (204) based on the present operating condition and the future operating condition, each of the balancing targets being indicative of an energy storage unit characteristic to be balanced in order to achieve the balancing target type. There is further provided to switch (S408) from balancing the energy storage module according to the first balancing target type to balancing the energy storage module according to the second balancing target type.