Integrating Energy Management and Yard Planner for Vehicle Configurations
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Solution Overview
Problem
Current transportation network systems face inefficiencies in coordinating vehicle selection and configuration for optimal energy efficiency and safety, particularly in vehicle yards where vehicles must be paired based on power and availability, leading to suboptimal routes and increased emissions.
Innovation Solution
A method and system that identifies suitable vehicles for a multi-vehicle system, determines potential builds based on sequential orders, simulates travel scenarios, calculates safety, consumption, and build metrics, and generates evaluations to select an optimal configuration for each trip, optimizing fuel efficiency and safety.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If vehicles are assigned or paired with payloads based on power or ability in vehicle yards, then vehicles can be matched to their capabilities, but energy efficiency and emission performance deteriorate due to ignoring overall energy efficiency and availability of vehicles in other yards
Solution Approach 1:
The patent combines the yard planner system and energy management system into an integrated system. The yard planner determines vehicle assignments based on power and ability, while the energy management system evaluates energy efficiency and emissions across the entire transportation network. This merging allows the system to maintain reliable vehicle-payload matching while optimizing for energy efficiency by considering vehicles in other yards.
Solution Approach 2:
The integrated system acts as an intermediary between the yard planner's vehicle assignment decisions and the energy management considerations. The energy management system provides feedback about energy efficiency and emissions, which influences the yard planner's vehicle selection, creating a mediating mechanism that balances capability matching with environmental performance.
2Productivity
If traditional vehicle assignment methods are used in vehicle yards, then vehicle availability is utilized, but productivity deteriorates due to suboptimal routes and increased build times
Solution Approach 1:
The system performs preliminary simulation of different vehicle builds and route options before final assignment. By evaluating multiple potential configurations in advance and selecting the optimal build, the system reduces actual build time and improves trip completion efficiency, avoiding suboptimal assignments that would require later adjustments.
Solution Approach 2:
The system dynamically evaluates vehicle assignments by simulating different build scenarios and selecting the optimal configuration based on real-time conditions. This dynamic approach allows the system to adapt vehicle assignments to current network conditions, reducing build times and improving productivity compared to static assignment methods.
Data Source
AI summary
A system and method identifies vehicles to be included in a multi-vehicle system that is to travel along one or more routes for an upcoming trip, and determines plural different potential builds of the multi-vehicle system. The different potential builds represent different sequential orders of the vehicles in the multi-vehicle system. The system and method also simulate travels of the different potential builds for the upcoming trip, calculate a safety metric, consumption metric, and/or build metric for the different potential builds based on travels that are simulated, and generates a quantified evaluation of the safety metric, consumption metric, and/or build metric for the different potential builds for use in selecting a chosen potential build of the different potential builds. The chosen potential build is used to build the multi-vehicle system for the upcoming trip.