Battery SOC Estimation Using Pulse-Duration Resistance Tables
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Solution Overview
Problem
Existing battery state of charge estimation methods in hybrid-electric and battery-electric vehicles are inaccurate due to the failure to account for changes in voltage drop caused by diffusion processes within the traction battery, particularly when current pulses vary in duration, leading to inconsistent resistance values and subsequent SOC calculations.
Innovation Solution
Implementing a controller that uses multiple resistance tables based on different current pulse durations to compensate for changes in voltage drop, with one table for short-term pulses and another for long-term pulses, selecting the appropriate table based on the duration of the current flow to accurately estimate the state of charge.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single resistance value is used for state of charge estimation, then the device complexity is reduced, but the measurement precision deteriorates due to inability to account for diffusion process variations
Solution Approach 1:
The patent divides the resistance characterization into multiple separate tables, each corresponding to a specific current pulse duration (e.g., 10 seconds, 60 seconds, 300 seconds). This segmentation allows the system to capture the varying resistance behavior under different diffusion process conditions without requiring a single complex model that would be difficult to implement and calibrate.
Solution Approach 2:
The patent implements a dynamic selection mechanism that automatically chooses the appropriate resistance table based on the actual current pulse duration detected during operation. This dynamic adaptation ensures that the most accurate resistance value is used for each specific operating condition, thereby maintaining high measurement precision across varying conditions without requiring all possible resistance values to be simultaneously active in the system.
2Measurement precision
If multiple resistance tables are used to account for different current pulse durations, then the measurement precision improves, but the device complexity increases
Solution Approach 1:
The patent pre-calculates and stores resistance values in multiple tables during the design and calibration phase, covering a range of current pulse durations and states of charge. This preliminary action eliminates the need for real-time complex calculations during operation, as the controller only needs to look up pre-computed values based on the measured current pulse duration, thereby reducing computational complexity while maintaining high precision.
Solution Approach 2:
The patent introduces an intermediary parameter - the current pulse duration - that serves as the key to selecting the appropriate resistance table. This intermediary simplifies the control logic by providing a clear, measurable criterion for table selection, avoiding the need for complex algorithms to determine which resistance value to use under varying operating conditions.
3Measurement precision
If resistance values are updated frequently to track diffusion processes, then the measurement precision improves, but the loss of time increases due to additional measurements
Solution Approach 1:
The patent employs periodic current pulses of specific durations (e.g., 10 seconds, 60 seconds, 300 seconds) to elicit resistance responses that correspond to different stages of the diffusion process. By using these standardized periodic measurements, the system captures the essential resistance behavior at key time points without requiring continuous monitoring, thereby achieving accurate state of charge estimation with minimal time investment.
Solution Approach 2:
The patent applies current pulses that are sufficiently long to reach the desired diffusion state (such as 300 seconds for steady-state conditions), even though shorter pulses might suffice for approximate measurements. This excessive action ensures that the resistance values captured truly represent the diffusion process at each stage, providing a safety margin that guarantees measurement accuracy without requiring multiple incremental measurements that would consume more time.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach improves the accuracy of battery state of charge estimation by accounting for varying resistance values resulting from diffusion processes, providing a more precise SOC calculation across different current pulse durations, thereby enhancing the management and operation of traction batteries.
Implementation Method 1
compensate for a change in voltage drop caused by diffusion processes within the traction battery
Data Source
AI summary
A vehicle includes a traction battery and a controller programmed to, in response to a duration of current flow through the traction battery exceeding a predetermined duration, output a state of charge based on a first resistance value that is greater than a second resistance value used when the duration is less than the predetermined duration to compensate for a change in voltage drop caused by diffusion processes within the traction battery.