Delivery Route Sequencing by Item Mass for Lower Energy Use
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Solution Overview
Problem
Existing vehicle delivery methods do not optimize energy efficiency based on the mass of items being transported, leading to inefficient energy consumption and range limitations.
Innovation Solution
A method and controller that determine the most energy-efficient delivery route by considering the mass of each item, optimizing parameters such as energy remaining, energy consumption, top speed, driving range, and number of trips by analyzing and programming the delivery order to reduce vehicle mass progressively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the vehicle delivers heavier items over longer distances, then the delivery capacity is improved, but the energy consumption increases and driving range is reduced
Solution Approach 1:
The system performs preliminary calculation of multiple delivery routes considering item masses and distances before actual delivery. By pre-determining the optimal sequence that minimizes energy consumption while maintaining delivery capacity, the vehicle can execute the pre-planned efficient route without real-time optimization overhead.
Solution Approach 2:
The system changes the delivery sequence parameter based on item mass characteristics. Heavier items are delivered to closer destinations first, while lighter items are delivered to farther destinations, optimizing the energy consumption parameter throughout the delivery journey.
2Ease of operation
If the vehicle delivers items in a fixed sequence, then the routing simplicity is improved, but the energy efficiency is reduced
Solution Approach 1:
The system dynamically changes the delivery sequence parameter based on item mass and destination distance. By adjusting the delivery order to deliver heavier items first and lighter items later, the vehicle optimizes energy efficiency while maintaining operational simplicity through automated route calculation.
3Quantity of substance
If the vehicle carries more items, then the delivery volume is improved, but the energy consumption per item increases
Solution Approach 1:
The system pre-calculates the optimal delivery sequence for all items in the vehicle, considering their individual masses and destination distances. This preliminary optimization ensures that the vehicle maximizes its item capacity while minimizing total energy consumption, thereby reducing energy per item.
4Productivity
If the vehicle makes multiple trips to deliver all items, then the delivery completeness is improved, but the total energy consumption increases
Solution Approach 1:
The system optimizes the delivery sequence parameter to ensure all items are delivered in a single trip when possible. By carefully arranging the delivery order based on item mass and distance, the vehicle maximizes its cargo utilization and minimizes the need for multiple trips, thereby reducing total energy consumption.
Data Source
AI summary
A plurality of items includes a first item deliverable to a first delivery destination and a second item deliverable to a second delivery destination. The value of a first vehicle parameter dependent on a mass of the first item and a mass of the second item is calculated for a first delivery route, the first delivery route being configured to stop at the first delivery destination before the second delivery destination to thereby deliver the first item before the second. The value of a first vehicle parameter for a second delivery route is calculated, the second delivery route being configured to stop at the second delivery destination before the first delivery destination to thereby deliver the second item before the first. A delivery route is determined that comprises the first and second delivery destinations that optimizes the value of the first vehicle parameter.