Dynamic Vehicle Trip Planning for Fuel Efficiency
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Solution Overview
Problem
Existing vehicle trip planning methods often result in inefficiencies due to static speed management, which fails to account for dynamic environmental and vehicle parameters, leading to increased fuel consumption and reduced travel times.
Innovation Solution
A method and system that determine the relationship between moving resistance and vehicle characteristics to generate dynamic trip plans, varying drag coefficients based on speed restrictions and environmental factors, allowing for adaptive speed adjustments to optimize fuel efficiency and travel times.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If static speed limits are maintained for each section of the route, then the vehicle system can simplify control and planning, but fuel efficiency deteriorates and energy consumption increases
Solution Approach 1:
The patent applies dynamics by transitioning from static speed limits to dynamic speed profiles that adjust in real-time based on environmental conditions, vehicle characteristics, and route parameters. The trip algorithm continuously calculates optimal speeds considering changing factors such as terrain, weather, and traffic, allowing the vehicle to adapt its speed dynamically rather than following fixed section-based limits.
Solution Approach 2:
The patent implements parameter changes by modifying multiple variables including speed, acceleration, and drag coefficients based on real-time conditions. The trip algorithm adjusts these parameters continuously to optimize fuel efficiency, such as varying drag coefficients according to environmental factors and changing vehicle operational states, rather than maintaining constant parameters throughout the trip.
2Device complexity
If static speed limits are used for route sections, then the trip plan can be simpler to generate, but travel time increases due to inefficiencies
Solution Approach 1:
The system employs dynamic speed profiles that continuously adapt to current conditions, enabling the vehicle to maintain optimal speeds for minimizing travel time while accounting for real-time factors. This dynamic approach allows the vehicle to accelerate more aggressively when conditions permit and coast or decelerate when beneficial, rather than adhering to conservative static speed limits.
Solution Approach 2:
The trip algorithm maintains continuous optimization of vehicle operation throughout the journey, constantly adjusting speed and other parameters to minimize travel time. This continuous adaptation ensures that the vehicle is always operating at or near optimal efficiency points, rather than transitioning between fixed speed zones, thereby reducing unnecessary delays and maintaining smoother, more efficient travel.
3Power
If static speed management is implemented, then the vehicle system can reduce computational requirements, but fuel consumption increases due to inability to adapt to changing conditions
Solution Approach 1:
The patent implements dynamic trip planning that continuously calculates optimal operational parameters based on real-time data from sensors and external sources. The system processes changing environmental conditions, vehicle state, and route information to dynamically adjust speed profiles and operational settings, enabling adaptive fuel efficiency optimization without requiring excessive computational resources through efficient algorithm design.
Solution Approach 2:
The trip algorithm incorporates feedback mechanisms that continuously monitor actual vehicle performance, environmental conditions, and route parameters. This feedback loop allows the system to learn from actual trip data and adjust future trip plans accordingly, optimizing fuel consumption through data-driven decisions while managing computational requirements through iterative improvement rather than exhaustive calculation.
4Device complexity
If drag coefficients are kept constant, then the calculations for trip planning are simpler, but accuracy deteriorates when environmental factors change
Solution Approach 1:
The patent implements variable drag coefficients that change based on environmental factors such as weather conditions, terrain characteristics, and vehicle operational state. The trip algorithm adjusts drag coefficients dynamically to reflect actual resistance conditions, improving the accuracy of fuel consumption calculations and trip planning without requiring overly complex computational models through targeted parameter adaptation.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enhances fuel efficiency and reduces emissions by dynamically adjusting vehicle speed according to changing conditions, improving travel times and operational efficiency compared to static speed management.
Implementation Method 1
determining a relationship between an air resistance of a vehicle system and one or more characteristics of the vehicle system. The relationship may include at least one drag coefficient.
Data Source
AI summary
A system and method that includes determining a relationship between a moving resistance of a vehicle system and one or more characteristics of the vehicle system. A trip plan may be generated based at least in part on the relationship for movement of the vehicle system through one or more sections of one or more routes based at least in part on the relationship. One or more operational settings of the vehicle system are then designated for implementing the trip plan to drive movement of the vehicle system to achieve one or more objectives.