Hybrid Vehicle Battery SOC Control via Predictive Slope Analysis
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Solution Overview
Problem
Hybrid vehicles face challenges in optimizing battery state of charge (SOC) during cruise travel, leading to unnecessary energy consumption and inefficiencies due to the battery reaching a fully charged state, which limits regenerative braking and causes speed control issues.
Innovation Solution
A method and device using a controller to predict the SOC change slope through regression analysis, determining when to switch between motor and engine operation to maintain the SOC within a normal range, ensuring efficient energy use and optimal operating points for cruise travel.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If the battery is charged to maximum capacity during cruise travel, then the energy storage capability is improved, but regenerative braking becomes limited and speed control issues occur
Solution Approach 1:
The system performs preliminary prediction of battery SOC during cruise travel using regression analysis, determining the change slope and projecting future SOC values. This allows the control system to take advance action by switching to motor-only operation before the battery reaches full charge, preventing the condition where regenerative braking becomes limited.
Solution Approach 2:
The system dynamically adjusts the driving mode based on real-time battery SOC conditions. When predicted SOC reaches the maximum threshold, the system transitions from hybrid operation to motor-only operation. This dynamic adaptation ensures the battery remains within optimal charge ranges, maintaining both energy storage capability and regenerative braking reliability.
2Use of energy by moving object
If the battery SOC is maintained within a normal range through predictive control, then energy efficiency is improved, but the system complexity increases due to regression analysis and predictive algorithms
Solution Approach 1:
The system implements feedback control by continuously monitoring actual battery SOC during cruise travel and comparing it with predicted SOC values. The regression analysis model uses measured SOC data to calculate change slopes and update predictions. This feedback mechanism enables energy-efficient operation while using established computational methods that balance accuracy with implementation feasibility.
Solution Approach 2:
The control system uses the battery's own SOC data and operational patterns to generate predictions and make control decisions. By leveraging regression analysis on historical SOC measurements, the system serves itself by identifying optimal operating points without requiring external intervention or overly complex control architectures.
3Productivity
If the hybrid vehicle switches between engine and motor operation based on predicted SOC, then the energy management is optimized, but the control complexity increases
Solution Approach 1:
The system performs preliminary switching decisions based on predicted SOC trajectories rather than waiting for threshold violations. By calculating the change slope of SOC during cruise travel and projecting future values, the system determines optimal switch points in advance, transitioning from engine-motor hybrid operation to motor-only operation before battery full-charge conditions occur.
Solution Approach 2:
The system changes operational parameters (driving mode, power distribution) based on predicted SOC parameters. When the predicted SOC reaches the maximum threshold, the control system changes the operating state from hybrid mode to electric-only mode. This parameter-based control approach optimizes energy management while using clear, definable switching criteria.
Data Source
AI summary
A method for controlling a state of charge (SOC) of a battery for a cruise travel of a hybrid vehicle includes predicting, by a controller, the SOC of the battery including a change slope of the SOC of the battery for the cruise travel based on a measured value of the SOC. The method includes determining, by the controller, whether the predicted SOC of the battery is equal to or greater than a maximum value of a normal range of the battery when the change slope of the SOC is greater than zero. The method includes driving, by the controller, only a driving motor of the hybrid vehicle whereby the driving motor uses electric power of the battery when the predicted SOC of the battery reaches the maximum value of the normal range of the battery. The normal range of the battery is a region required for the cruise travel of the hybrid vehicle.