Battery Electric Machine Wake-Up Timing for Low-Power Idle
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Solution Overview
Problem
Battery Electric Machines (BEMs) face challenges in managing energy use during unpredictable work conditions, leading to potential energy depletion during extended stops, which can result in insufficient energy for continued operation or the need to enter a low power mode, affecting productivity and payload capacity.
Innovation Solution
A system and method that determines the location of a BEM, identifies compatible charging stations, predicts task durations and energy use, segments tasks into intervals, and optimally exits the low power mode based on predicted energy requirements to ensure timely resumption of operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If the BEM enters a low power mode to minimize energy use during extended idle periods, then energy consumption is reduced, but productivity decreases due to delayed resumption of operations
Solution Approach 1:
The system performs preliminary actions by predicting future task requirements and proactively exiting low power mode in advance of when work is needed. The controller predicts energy consumption patterns and schedules mode transitions before actual work demands occur, ensuring the BEM is ready to resume operations without delay while minimizing unnecessary energy consumption during idle periods.
Solution Approach 2:
The system dynamically adjusts the BEM's power mode based on predicted work demands. Rather than using a static low power mode strategy, the controller continuously monitors predicted energy consumption patterns and dynamically transitions between low power and active modes optimally, balancing energy conservation with productivity requirements based on real-time predictions.
2Productivity
If the BEM uses smaller batteries to optimize productive capacity, then payload capacity increases, but energy availability during unpredictable work conditions decreases
Solution Approach 1:
The system performs preliminary energy management by predicting future energy consumption requirements and proactively managing battery charge levels. The controller forecasts energy needs based on predicted work conditions and ensures sufficient charge is available before critical moments, allowing smaller batteries to reliably support optimized productive capacity without risking energy depletion during unpredictable stops.
Solution Approach 2:
The system uses feedback from predicted energy consumption patterns to continuously adjust battery management strategies. By monitoring predicted work conditions and actual energy usage, the controller adapts its energy management approach to ensure reliable energy availability while maintaining optimal battery sizing for productive capacity, creating a closed-loop system that balances these competing requirements.
3Productivity
If the BEM remains in active mode to ensure immediate resumption of operations, then productivity is maintained, but energy consumption increases during idle periods
Solution Approach 1:
The system performs preliminary analysis of predicted work demands to determine the optimal timing for exiting low power mode. By forecasting when work will resume and calculating the minimum energy consumption pattern, the controller schedules mode transitions in advance, ensuring productivity is maintained without unnecessarily extending active mode duration during idle periods.
Solution Approach 2:
The system uses its own predictive capabilities to automatically manage its power state without external intervention. The controller self-determines when to exit low power mode based on its predictions of work demands and energy consumption patterns, optimizing the balance between maintaining productivity and minimizing energy consumption during idle periods.
Data Source
AI summary
A system and method for exiting a low power mode of operation of a battery electric machine (BEM) are provided. The method includes determining a location of a BEM allocated to a production circuit; determining a location of a charging station compatible with the BEM; based on the locations of the BEM and the charging station and the production circuit: determining a plurality of tasks of the BEM for executing the production circuit, predicting a corresponding duration and a corresponding energy use of each of the plurality of tasks, and determining a sequence of the plurality of tasks; initiating the BEM to perform a next task after a current task of the plurality of tasks; and causing the BEM to exit a low power mode of operation of the BEM based on the predicted corresponding durations and the predicted corresponding energy uses of the current task and the next task.