Battery-Aware Rail Path Planning for Transport Vehicles
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Solution Overview
Problem
Existing automated transport systems in semiconductor manufacturing struggle to determine an optimal path for transport vehicles equipped with batteries, especially when navigating between powered and non-powered sections of the rail, as they do not adequately consider the costs associated with charging and discharging.
Innovation Solution
A path finding method and apparatus that calculates costs between waypoints to a destination using a cost function incorporating amounts of charging and discharging, and determines an optimal path based on these calculated costs, utilizing an overhead hoist transport control system to manage transport vehicles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If transport vehicles use batteries to travel on non-powered sections of the rail, then the vehicles can operate independently of power lines, but the battery consumes energy and reduces operational duration
Solution Approach 1:
The system performs preliminary charging of batteries when transport vehicles are on powered sections of the rail, before they need to travel on non-powered sections. The OCS calculates optimal paths that include charging opportunities in advance, ensuring batteries are recharged before depletion occurs during battery-powered travel segments.
2Loss of time
If the transport system optimizes for shortest path, then travel time is reduced, but energy consumption increases due to frequent charging/discharging cycles
Solution Approach 1:
The OCS dynamically changes the cost parameters in the pathfinding algorithm to account for energy consumption. Instead of using only distance or time as the cost metric, the system incorporates energy consumption estimates based on battery state, power availability at different locations, and charging/discharging efficiency. This allows the system to select paths that balance travel time with energy conservation.
3Productivity
If the system calculates detailed cost functions including charging/discharging amounts, then path optimization improves, but computational complexity increases
Solution Approach 1:
The OCS divides the rail network into discrete segments with specific characteristics (powered sections, non-powered sections, charging availability). The pathfinding algorithm processes these segmented sections sequentially, calculating energy consumption for each segment based on vehicle battery state and segment properties. This segmentation approach breaks down the complex optimization problem into manageable sub-problems that can be solved efficiently.
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 solution enables transport vehicles to efficiently navigate the rail network by optimizing paths based on energy usage, thereby extending battery life and improving overall system efficiency.
Implementation Method 1
The transport vehicles are equipped with batteries internally, allowing them to use the energy stored in the batteries to move when traveling on track rails where the power lines are not installed
Data Source
AI summary
A path finding method capable of determining an optimal path for a transport vehicle equipped with a battery is provided. The path finding method includes: setting a destination for a transport vehicle using a battery; calculating costs between waypoints to the destination using a cost function, which includes amounts of charging and discharging occurring between the waypoints as an input variable; and determining a path to the destination based on the calculated costs.