Electric Vehicle Eco-Driving Assistance System
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Solution Overview
Problem
Drivers of electric vehicles face challenges in maintaining environmentally friendly driving habits due to unexpected variables and traffic situations, despite understanding eco-friendly driving techniques, as existing technologies rely solely on vehicle hardware and changes in driving habits without real-time assistance.
Innovation Solution
A system that collects and processes real-time information including vehicle, geographic, and driver data to calculate and optimize energy-efficient routes, control vehicle components, and adjust driving modes for reduced energy consumption and air pollution, using a combination of information collecting, control logic, route setting, and vehicle driving controller sections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If drivers rely only on vehicle hardware and changes in driving habits, then eco-friendly driving techniques can be understood, but consistent environmentally friendly driving cannot be maintained due to unexpected variables and traffic situations
Solution Approach 1:
The system continuously collects real-time information about traffic conditions, road geometry, vehicle state, and driver behavior, then provides feedback through route recommendations and driving assistance signals. This closed-loop feedback mechanism enables consistent eco-friendly driving by dynamically adjusting guidance based on actual conditions rather than relying solely on pre-programmed driving habits.
Solution Approach 2:
The eco-driving assistance system acts as an intermediary between the driver, vehicle, and environment. It processes information from multiple sources (traffic data, road information, vehicle sensors) and translates this into actionable recommendations that help the driver adapt to unexpected situations while maintaining environmentally friendly driving patterns.
2Productivity
If real-time information collection and processing systems are implemented, then energy-efficient routes and driving parameters can be optimized, but system complexity increases
Solution Approach 1:
The system integrates multiple functions into a unified platform: route calculation, real-time traffic monitoring, vehicle state sensing, driver behavior analysis, and adaptive guidance all work together through a single integrated system. This multi-functionality reduces overall complexity compared to having separate systems for each function while maximizing energy efficiency benefits.
Solution Approach 2:
The information processing system is divided into modular components: information collection section, control logic section, route setting section, and vehicle driving controller. Each module handles specific tasks independently, making the overall complex system manageable and maintainable while achieving comprehensive energy optimization.
3Loss of energy
If comprehensive real-time monitoring and control is implemented, then energy consumption can be minimized by 4-7%, but information processing requirements and computational load increase
Solution Approach 1:
The system performs preliminary route calculation and energy optimization analysis before the vehicle journey begins, pre-processing traffic data and road information to identify energy-efficient routes. During actual driving, the system only needs to monitor real-time deviations and make minor adjustments, significantly reducing continuous computational load while maintaining optimal energy consumption.
Data Source
AI summary
A system and a method of assisting a driver in driving an electric vehicle in a more environmentally efficient manner are disclosed. In particular, an information collecting section collects information operating the electric vehicle and a control logic section generates control logic and models related to route calculation to a destination and operation of the electric vehicle based on the collected information. A route setting section calculates a plurality of travel routes based on the control logic and the model related to the route calculation and sets an optimum travel route having the highest energy efficiency among the plurality of travel routes. A vehicle driving controller monitors the vehicle state and controls driving of the electric vehicle based on the control logic and the model related to the driving of the electric vehicle when the electric vehicle travels along the optimum travel route set by the route setting section.