EV Range Estimation Using OCV-Q Battery Energy Modeling
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Solution Overview
Problem
Existing methods for calculating the endurance mileage of electric vehicles are inaccurate due to the non-linear relationship between state of charge (SOC) and driving range, influenced by various factors such as driving habits, road conditions, vehicle characteristics, and battery internal factors.
Innovation Solution
A method and apparatus that calculate energy consumption per unit mileage and use an OCV-Q reference curve to determine the current remaining available energy, incorporating real-time interaction with a cloud server to improve accuracy, with formulas DK=αDstd+βDactual+γDK-1 and Eremaining=∫0QremainingOCV(Q)dQ, to calculate the endurance mileage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the endurance mileage is directly estimated based on SOC using a piecewise monotonic linear relationship, then the calculation process is simple and fast, but the accuracy of the driving range prediction is low
Solution Approach 1:
The patent changes the estimation approach from direct SOC-based linear estimation to a multi-parameter integration method. It introduces energy consumption per unit mileage as a dynamic parameter that varies with operating conditions, and uses OCV-Q curves to establish a non-linear relationship between battery state and remaining capacity. This transforms the single-parameter SOC estimation into a multi-parameter calculation involving OCV, energy consumption rates, and capacity curves, thereby improving accuracy while maintaining computational efficiency through pre-stored lookup tables.
2Measurement precision
If multiple factors affecting endurance mileage are considered (operating conditions, vehicle factors, battery internal factors), then the driving range prediction accuracy is improved, but the calculation complexity increases
Solution Approach 1:
The patent segments the complex endurance mileage calculation into three independent modules: (1) OCV-based remaining capacity estimation using pre-stored OCV-Q curves, (2) energy consumption per unit mileage calculation based on operating conditions, and (3) final endurance mileage computation by integrating remaining capacity and energy consumption. Each module handles specific factors independently, allowing complex multi-factor analysis to be broken down into manageable segments that can be processed separately and then combined, thus reducing overall system complexity while maintaining comprehensive accuracy.
Solution Approach 2:
The patent performs preliminary actions by pre-calculating and storing OCV-Q reference curves, energy consumption characteristics under various operating conditions, and battery capacity data before actual endurance mileage calculation. These pre-stored data structures and characteristic curves are prepared in advance and stored in the battery management system, so that during actual operation, the system only needs to query and interpolate from these pre-computed data rather than performing complex real-time calculations, thereby reducing online computational complexity while maintaining high accuracy.
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 provides a more accurate calculation of endurance mileage by considering multiple influencing factors, enhancing the precision of driving range predictions and providing a data platform for big data applications.
Implementation Method 1
obtaining an open circuit voltage (OCV)-battery capacity Q reference curve of the power battery; obtaining an OCV of the power battery; obtaining current remaining available energy of the power battery according to the OCV and the OCV-Q reference curve of the power battery
Data Source
AI summary
Provided is an electric vehicle driving mileage calculation method, comprising the following steps: calculate the energy consumption of a power battery of the electric vehicle per unit driving mileage; obtain the open-circuit voltage (OCv)-battery capacity (Q) reference curve of the power battery; obtain the OCv of the power battery; obtain the currently remaining available energy of the power battery according to the OCv and the OCv-Q reference curve of the power battery; calculate the driving mileage of the electric vehicle according to the energy consumption of the power battery per unit driving mileage and the currently remaining available energy of the power battery, whereby the driving mileage of the electric vehicle which is calculated is more accurate. Also disclosed is an electric-vehicle driving mileage calculation device and an electric vehicle.