Vehicle Driving Control Optimizing Battery Energy Efficiency
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Solution Overview
Problem
Conventional cruise control systems are insufficient in terms of energy efficiency, particularly for electric vehicles, which is a concern as the world shifts towards eco-friendly vehicles and aims to reduce CO2 emissions.
Innovation Solution
A vehicle driving control method that optimizes energy efficiency by obtaining a state variable model of longitudinal dynamics, calculating wheel and battery power, and outputting a wheel drive control target using an approximated battery power function as an objective function, with constraints such as average velocity and safe distance from a preceding vehicle, to achieve optimal traction and braking forces.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional cruise control is designed for driving convenience and safety, then driving convenience and safety are improved, but energy efficiency deteriorates
Solution Approach 1:
The patent changes the control parameters from simple velocity-based cruise control to a comprehensive state variable model that includes velocity, acceleration, battery state of charge, road gradient, and curvature. This allows the system to optimize energy consumption by adjusting driving parameters based on multiple factors rather than just maintaining a set speed.
Solution Approach 2:
The system performs preliminary calculations of wheel power and battery power requirements before actual driving control. By pre-computing the optimal control targets using an approximated battery power function, the system can proactively adjust driving behavior to minimize energy consumption while maintaining safety and comfort.
2Reliability
If conventional cruise control is designed for driving safety, then safety is improved, but energy efficiency deteriorates
Solution Approach 1:
The patent incorporates safety constraints into the energy optimization framework by maintaining velocity and acceleration limits that ensure safe driving. The state variable model includes safety-relevant parameters while the control algorithm simultaneously optimizes for energy efficiency, achieving both safety and energy savings.
Solution Approach 2:
The system uses feedback from multiple sensors (velocity, acceleration, battery state, road conditions) to continuously adjust the control target. This feedback mechanism ensures that safety requirements are met while dynamically optimizing energy consumption based on real-time driving conditions.
3Use of energy by moving object
If battery technology is developed to improve energy efficiency, then energy efficiency is improved, but device complexity increases
Solution Approach 1:
The patent replaces complex battery hardware modifications with a software-based control strategy. By using an approximated battery power function and optimization algorithms, the system achieves energy efficiency improvements through intelligent control rather than through complex battery technology changes, thus avoiding increased device complexity.
Solution Approach 2:
The control system acts as an intermediary between the battery and the driving dynamics. Rather than modifying the battery itself, the system introduces a control layer that optimizes power delivery and consumption, achieving energy efficiency improvements without increasing battery technology complexity.
4Use of energy by moving object
If driving control technology is added to improve energy efficiency, then energy efficiency is improved, but device complexity increases
Solution Approach 1:
The control system is designed to perform multiple functions: it maintains cruise control functionality for driver convenience, ensures safety through velocity and acceleration constraints, and optimizes energy consumption. By combining these functions into a single unified control algorithm, the patent avoids the need for separate complex control systems for each function.
Solution Approach 2:
The patent transforms the control approach from simple velocity regulation to a multi-parameter optimization problem. By using a state variable model that incorporates velocity, acceleration, battery state, and road conditions, the system achieves energy efficiency through parameter optimization rather than through complex additional hardware or control mechanisms.
Data Source
AI summary
A vehicle driving control method with optimal efficiency includes a first step of state variable modeling of a longitudinal dynamics equation of a vehicle based on a velocity-related state variable and a wheel drive input variable, a second step of calculating wheel power using the state variable and the input variable, a third step of calculating battery power using the wheel power calculation, a fourth step of approximating the battery power, and a fifth step of outputting a wheel drive control target by calculating a minimum solution by using the approximated battery power as an objective function and applying at least one constraint to the objective function.