Battery Queue Positioning for Mine Machines With Task-Aware SOC Control
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Solution Overview
Problem
Battery electric vehicles at mine sites face limited battery capacity issues, leading to energy depletion while waiting in queues, which can prevent them from completing tasks or dropping below optimal charge levels, as existing systems like the '161 patent do not account for post-charging tasks or future task planning.
Innovation Solution
A method and system that determine estimated energy depletion and state of charge (SOC) to position machines in a queue such that they arrive with sufficient energy to complete tasks, using queue managers and sensors to optimize queue placement based on battery-related characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If machines wait in queue for charging following existing scheduling methods, then charging can be performed when near chargers, but energy depletion occurs during waiting that prevents completion of assigned tasks or drops battery charge below optimal levels
Solution Approach 1:
The system performs preliminary calculation of energy depletion during queue waiting time before the machine actually waits. The queue manager determines the estimated amount of energy depletion based on current SOC, desired SOC, and expected wait time, then adjusts the charging schedule in advance to ensure sufficient energy remains for post-charging tasks.
Solution Approach 2:
The system continuously monitors battery SOC and provides feedback to the queue manager. The queue manager uses this feedback to adjust queue positioning and charging schedules dynamically, ensuring that energy depletion during waiting does not compromise task completion capability.
2Ease of operation
If machines are positioned at the end of the queue, then charging schedule can be calculated based on current and desired SOC, but energy is depleted during waiting time
Solution Approach 1:
The system dynamically adjusts queue positioning based on real-time SOC measurements and predicted energy depletion. Instead of fixed queue positions, the queue manager continuously optimizes positioning to balance charging efficiency with energy conservation during waiting, adapting to changing battery states and task requirements.
3Productivity
If queue position is optimized for charging efficiency, then charging can be performed effectively, but future task energy requirements may not be met
Solution Approach 1:
The system performs preliminary assessment of future task energy requirements before determining queue position. The queue manager calculates the energy needed for post-charging tasks and uses this information to adjust charging schedules and queue positioning in advance, ensuring that optimized charging does not compromise future task completion.
Solution Approach 2:
The system incorporates feedback loops that continuously monitor SOC and compare it against required SOC for future tasks. The queue manager uses this feedback to dynamically adjust queue positioning and charging parameters, balancing charging efficiency with the reliability of future task completion.
Data Source
AI summary
Systems and methods can position or provide a mobile machine in a queue of a plurality of the mobile machines such that an estimated future amount of energy of an energy source if the mobile machine is at or above a required amount of energy of the energy source to complete a predetermined task after the mobile machine reaches an end of the queue. Such positioning or providing can include or be moving the mobile machine up or forward in the queue from a condition where the estimated future amount of energy of the energy source is less than the required amount of energy of the energy source to complete the predetermined task after the mobile machine reaches the end of the queue.