Hybrid Vehicle Driving Mode Control Using Traffic Data
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Solution Overview
Problem
Conventional hybrid vehicles lack an efficient driving mode control strategy that optimizes fuel efficiency based on route information and traveling conditions, leading to reduced fuel efficiency due to fixed reference values and manual mode selection.
Innovation Solution
An apparatus and method that calculates driving mode data using traffic information and vehicle dynamics algorithms to determine the optimal power distribution ratio between motor torque and engine torque, allowing the vehicle to actively switch between EV and HEV modes based on real-time traffic conditions and battery state, thereby optimizing fuel efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If fixed reference values or manual method are used to switch driving mode, then the control system is simple, but the fuel efficiency is reduced due to inability to optimize for route
Solution Approach 1:
The system pre-calculates optimal driving mode data before vehicle operation by analyzing traffic information from current position to destination. The driving mode data calculation unit computes power distribution ratios and mode switching points in advance based on route characteristics, eliminating the need for complex real-time optimization during vehicle operation while maximizing fuel efficiency.
Solution Approach 2:
The system dynamically adjusts driving mode based on actual traveling conditions by comparing real-time vehicle state (speed, acceleration, battery charge) with pre-calculated optimal driving mode data. The driving control unit continuously determines appropriate driving modes by applying current traveling conditions to the pre-computed data, enabling adaptive optimization without complex real-time calculations.
2Use of energy by moving object
If real-time traffic information and vehicle dynamics algorithms are used to calculate optimal driving mode, then fuel efficiency is improved, but the computational complexity increases
Solution Approach 1:
The system performs computationally intensive calculations of optimal power distribution ratios and mode switching points before vehicle operation using traffic information and vehicle dynamics algorithms. By pre-calculating driving mode data offline, the system avoids complex real-time computations during vehicle operation, reducing onboard computational requirements while maintaining optimal fuel efficiency.
Solution Approach 2:
The system uses lightweight dynamic adjustment during operation by comparing real-time vehicle state with pre-calculated optimal data. The driving control unit determines appropriate modes through simple comparison and selection based on current traveling conditions, avoiding complex real-time optimization algorithms while achieving adaptive fuel efficiency optimization.
3Use of energy by moving object
If driving mode is optimized for specific route, then fuel efficiency improves, but the system cannot adapt to changing traffic conditions
Solution Approach 1:
The system dynamically adapts to changing traffic conditions by continuously monitoring actual vehicle state (speed, acceleration, battery charge level) and comparing it with pre-calculated optimal driving mode data. The driving control unit adjusts driving mode in real-time based on this comparison, enabling the system to adapt to unexpected conditions while maintaining the fuel efficiency benefits of pre-optimized route planning.
Solution Approach 2:
The system implements feedback control by continuously monitoring actual traveling conditions and comparing them with the pre-calculated optimal driving mode data. The driving control unit uses this feedback to determine appropriate driving modes, allowing the system to adapt to changing conditions while maintaining optimal fuel efficiency through continuous adjustment based on actual vehicle state.
Data Source
AI summary
A control apparatus for controlling a vehicle includes a driving motor configured to drive the vehicle by outputting motor torque based on a supply voltage from a battery, and an engine configured to drive the vehicle by outputting engine torque. The control apparatus may acquire driving mode data which is calculated based on traffic information from the current position to the destination of the vehicle and dimension information of the vehicle, and control the vehicle to drive to the destination according to a driving mode which is determined by applying a travelling condition of the vehicle to the acquired driving mode data, where the power distribution ratio of the motor torque to the engine torque is reflected in the driving mode data.