Vehicle Battery SOC Estimation via Multi-Module Sampling
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Solution Overview
Problem
Existing methods for estimating the state-of-charge (SOC) of vehicle batteries, such as those in hybrid electric vehicles, face inaccuracies due to processor speed disparities between control modules, leading to incomplete accounting of energy consumption and generation, which can result in battery undercharging or overcharging and diminished battery life.
Innovation Solution
A method that determines an initial SOC value based on standard readings from a battery control module at a slow sampling rate and adjusts it with data from faster sampling rate readings from other control modules, such as brake and suspension control modules, to account for energy changes between sampling intervals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If data is gathered at a slow sampling rate to reduce processing load, then device complexity and energy consumption are reduced, but measurement precision and reliability of SOC estimation deteriorate due to missing fast energy consumption events
Solution Approach 1:
The SOC estimation process is segmented into two distinct sampling rate layers: a slow sampling rate for general SOC calculation and a fast sampling rate for capturing rapid energy consumption events. This segmentation allows each layer to operate optimally without requiring the entire system to run at high processing speeds, thus reducing overall device complexity while maintaining measurement precision through the complementary fast-sampling adjustment
Solution Approach 2:
The patent merges data from two different sampling rate sources (slow and fast) into a unified SOC estimation. The fast-sampling data is used to generate an adjustment factor that corrects the slow-sampling SOC estimate, combining the benefits of low processing load with high measurement accuracy in a single integrated estimation process
2Measurement precision
If data is gathered at a fast sampling rate to improve SOC estimation accuracy, then measurement precision improves, but device complexity and energy consumption increase due to higher processing requirements
Solution Approach 1:
Instead of continuously gathering data at fast sampling rates for all calculations, the patent applies fast-sampling data partially and selectively - only to generate an adjustment factor for specific rapid energy consumption events. This partial action approach achieves the necessary measurement precision improvement without the full burden of continuous high-speed processing across the entire system
Solution Approach 2:
The fast-sampling data acts as an intermediary that indirectly improves SOC estimation accuracy. Rather than using fast-sampling data for the entire SOC calculation, it serves as a mediator to generate an adjustment factor that corrects the slow-sampling estimate, thus achieving high precision without requiring the main processing system to operate at high speeds
3Use of energy by moving object
If the battery control module operates at a slow processor speed to reduce energy consumption, then energy efficiency improves, but reliability of energy accounting deteriorates due to inability to account for all energy consumption by fast-operating devices
Solution Approach 1:
The patent implements a feedback mechanism where fast-sampling data from other control modules is fed back to the battery control module as an adjustment factor. This feedback loop allows the slow-operating battery control module to compensate for missed energy consumption events, maintaining reliable energy accounting without requiring the battery control module itself to operate at high speeds
Solution Approach 2:
The adjustment factor derived from fast-sampling data serves as an intermediary that bridges the gap between slow battery control module processing and fast energy consumption events. This intermediary mechanism allows accurate energy accounting to occur indirectly through mathematical correction rather than direct real-time measurement, preserving reliability while maintaining low energy consumption
Data Source
AI summary
A method and system for accurately estimating one or more vehicle battery parameters, such as state-of-charge (SOC). In an exemplary embodiment, a battery control module gathers standard battery readings for estimating SOC at a relatively slow sampling rate. The battery control module receives adjustment data from one or more control modules located around the vehicle, where the control modules gather readings at faster sampling rates and then provide the information to the slower battery control module. The adjustment data from the faster control modules is representative of energy consumption and/or generation events that occur in between the readings taken by the battery control module at the slower sampling rate, and enable the method to make a more accurate and complete estimate of SOC.