Two-Part Error Model for Battery SOC Accuracy

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Solution Overview

Problem

Existing methods for determining the state of charge (SOC) of electrical energy storage units in vehicles are inaccurate, leading to potential breakdowns and inefficient energy management due to model errors, which are not effectively accounted for in current technologies.

Innovation Solution

A two-part mathematical error model is introduced, comprising a static submodel for open-circuit voltage characteristics and a dynamic submodel for voltage characteristics based on electrical current, allowing for the determination of model errors and improving SOC accuracy by considering both static and dynamic errors.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If model-based state determination is used to improve SOC accuracy, then measurement precision is improved, but reliability deteriorates due to unaccounted model errors

Engineering Contradiction:
ImproveSOC determination accuracyVSAvoidoperational safety
Core Design Contradiction:
Measurement precisionVSReliability

Solution Approach 1:

The patent implements a feedback mechanism by continuously determining model errors based on the difference between measured and calculated values, then using this error information to adjust and improve the accuracy of state determination results in real-time

Inventive Principle:
Principle #23Feedback

Solution Approach 2:

The patent applies prior cushioning by establishing conservative safety margins in advance based on determined model errors, preparing compensation measures before actual failures occur to prevent breakdowns and abrupt shutdowns

Inventive Principle:
Principle #11Beforehand cushioning (Prior cushioning)

2Reliability

If conservative range calculations are used to ensure safety, then reliability is improved, but loss of energy increases due to wasted range

Engineering Contradiction:
Improveoperational safetyVSAvoidwasted range
Core Design Contradiction:
ReliabilityVSLoss of energy

Solution Approach 1:

The patent applies dynamics by making safety margins and voltage limits dynamic rather than static, adjusting them in real-time based on determined model errors and current operating conditions, allowing the system to optimize between safety and energy utilization

Inventive Principle:
Principle #15Dynamics

3Reliability

If static voltage limits are used to prevent breakdowns, then reliability is improved, but productivity decreases due to reduced power and energy retrieval

Engineering Contradiction:
Improvebreakdown preventionVSAvoidpower retrieval
Core Design Contradiction:
ReliabilityVSProductivity

Solution Approach 1:

The patent transforms static voltage limits into dynamic limits that adapt in real-time based on determined model errors and operating conditions, enabling the system to safely operate at optimal power levels rather than conservative fixed limits

Inventive Principle:
Principle #15Dynamics

Data Source

PatentUS20230106946A1Method for determining a model error in a mathematical model of an electrical energy storage unit
Publication Date: 2023.04.06 ROBERT BOSCH GMBH
  • US20230106946A1 patent drawing
  • US20230106946A1 patent drawing

AI summary

The invention relates to a method for determining a model error in a mathematical model of an electrical energy storage unit, which method comprises the following steps: a) providing a mathematical error model for determining the model error in the mathematical model, wherein the mathematical error model is provided in at least a two-part form, wherein a first model error of an open-circuit voltage curve of the mathematical model of the electrical energy storage unit is modelled by the first part of the error model, and a second model error of a voltage curve of the mathematical model is modelled on the basis of an electrical current by the second part of the error model; b) determining at least one current value, wherein the electrical current flows in the electrical energy storage unit; c) applying the determined current value to the mathematical error model as the input value for the mathematical error model; d) determining the model error of the mathematical model as an output value for the mathematical error model, wherein the model error is dependent on the at least two part-models.