Driver Eco-Feedback Interface for Real-Time Route Energy Saving
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Solution Overview
Problem
Current energy consumption optimization methods for human-controlled vehicles do not consider real-time road conditions and traffic information, limiting their effectiveness in reducing fuel consumption and battery charging efficiency.
Innovation Solution
A method that receives data on road topology and real-time traffic information to determine an optimized driving pattern, which is then communicated to the driver through various feedback mechanisms, such as visual, acoustic, and haptic outputs, to adjust their driving behavior for improved energy efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If eco mode optimization depends only on engine characteristics, then the system is simple to implement, but it does not consider road conditions and cannot achieve real-time energy optimization
Solution Approach 1:
The system receives and stores road topology data (slopes, curves, surface conditions) in advance before the vehicle reaches those sections. This preliminary data collection allows the system to prepare optimized driving patterns ahead of time, enabling real-time adaptation without requiring complex real-time sensing and processing infrastructure
Solution Approach 2:
The patent introduces a navigation system as an intermediary component that provides road topology data to the energy optimization system. This mediator approach allows the system to access detailed road condition information without directly complex interactions with road infrastructure, simplifying the overall system architecture while enabling sophisticated energy optimization
2Loss of time
If route candidates are calculated prior to the start of the ride, then the calculation is simple, but the operation of the vehicle during the ride is not considered and optimization is not real-time
Solution Approach 1:
The system continuously outputs updated driving behavior recommendations throughout the ride as the vehicle progresses through different road sections. Rather than providing a single pre-calculated route, the system continuously adapts its recommendations based on the vehicle's current position and upcoming road topology, maintaining optimal energy efficiency throughout the entire journey
Solution Approach 2:
The route is divided into multiple segments based on road topology characteristics (slopes, curves, surface conditions). The system calculates and outputs optimized driving patterns for each segment separately, allowing real-time adaptation to changing road conditions while keeping computational complexity manageable through localized optimization
3Loss of energy
If the user receives detailed real-time driving behavior recommendations, then energy optimization is maximized, but the user interface complexity increases
Solution Approach 1:
The system provides continuous feedback to the user through the output unit, recommending specific driving behavior adjustments (acceleration, deceleration, gear selection) based on upcoming road sections. This feedback loop enables the user to easily adapt their driving behavior without requiring them to understand complex energy optimization calculations, maintaining interface simplicity while achieving energy savings
Data Source
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AI summary
The invention concerns a human machine interface, a transportation means and a method for optimizing energy consumption of a transportation means comprising the steps of receiving data (100) associated with a road topology of an upcoming route, determining (200) an optimized driving pattern with regard to energy consumption of the transportation means depending on the data and outputting (300) a recommendation of a driving behavior with respect to the transportation means to a user, wherein the recommendation of the driving behavior complies with the optimized driving pattern for a predetermined segment of the upcoming route in real time.