Vehicle Energy Allocation via Real-Time Environmental Data
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Solution Overview
Problem
Existing hybrid vehicle control systems do not utilize real-time or near real-time location and environmental data to optimize energy use, resulting in suboptimal fuel efficiency during normal operating conditions compared to test track performance.
Innovation Solution
A system that includes a central controller receiving positional and environmental data to calculate a desired energy allocation, which is then transmitted to the engine control system to optimize engine function, using GPS or cellular network data for precise location determination and incorporating terrain, weather, and traffic data for informed energy management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If real-time positional and environmental data are integrated into the control system, then fuel efficiency is improved, but device complexity increases
Solution Approach 1:
The control system is divided into multiple independent modules: a communication transponder for receiving positional data from GPS satellites, an environmental data acquisition system for gathering terrain and weather information, and a central controller for processing data and generating energy allocation commands. This segmentation allows each module to perform its specific function efficiently while reducing the overall complexity burden on any single component.
Solution Approach 2:
The system pre-acquires positional data from GPS satellites and environmental data from various sensors before the vehicle reaches specific conditions. By having this data ready in advance, the control system can make proactive energy allocation decisions rather than reactive adjustments, improving fuel efficiency while smoothing out the computational load and reducing peak complexity requirements.
2Measurement precision
If GPS and environmental sensors are added to the vehicle, then energy allocation accuracy is improved, but manufacturing cost increases
Solution Approach 1:
The communication transponder serves multiple functions: it receives positional data from GPS satellites, transmits vehicle operational data to external systems, and receives energy allocation commands. By making this single component multi-functional, the system achieves high measurement precision without proportionally increasing the number of separate components, thereby controlling manufacturing costs.
Solution Approach 2:
The patent introduces a central controller as an intermediary that processes raw positional and environmental data, converts it into meaningful energy allocation parameters, and transmits commands to the engine control system. This intermediary layer integrates multiple data sources and simplifies the interface requirements, reducing the need for expensive specialized components while maintaining high accuracy.
3Loss of energy
If real-time data processing is implemented, then fuel consumption is reduced, but computational requirements increase
Solution Approach 1:
The control system implements partial real-time processing by focusing computational resources on the most critical energy allocation decisions based on current positional and environmental data. Rather than continuously optimizing all vehicle parameters in real-time, the system applies intelligent algorithms selectively to high-impact parameters, reducing fuel consumption through targeted optimization while keeping computational requirements manageable.
Data Source
AI summary
Operating a vehicle includes receiving, by a central controller, positional data related to the vehicle and environmental data related to a current route of the vehicle. The central controller calculates a desired energy allocation based on the positional data and the environmental data, and transmits the desired energy allocation to the vehicle for use in controlling engine function.