Agricultural EV Charging Planning for Mid-Task Energy Interruptions
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Solution Overview
Problem
Electrically operated agricultural working vehicles face frequent and unpredictable energy depletion during tasks, leading to undesired workflow interruptions and increased driver burden due to the difficulty in estimating energy consumption for various agricultural operations.
Innovation Solution
A charging management method that estimates energy requirements based on specific task parameters, compares them with the current battery state, and optimally selects charging stations using criteria like accessibility, power, and price to minimize workflow interruptions by coordinating mobile supply vehicles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the agricultural working vehicle operates with a rechargeable electrical energy storage unit, then the vehicle can perform agricultural tasks autonomously, but the vehicle experiences frequent energy depletion requiring recharging interruptions
Solution Approach 1:
The control unit estimates the total energy requirement for the agricultural task in advance and compares it with the present state of charge before the task begins. This preliminary assessment allows the system to plan charging interruptions proactively rather than reactively, minimizing workflow disruptions by scheduling charges at optimal moments.
Solution Approach 2:
The system continuously monitors the state of charge of the electrical energy storage unit during task execution and compares it with the estimated energy consumption. This feedback mechanism enables real-time detection of energy depletion risks, triggering automated charging station selection and navigation to maintain continuous operation.
2Duration of action of moving object
If the vehicle carries a larger electrical energy storage unit to extend operation time, then the autonomous task performance improves, but the vehicle weight and energy consumption increase
Solution Approach 1:
The vehicle is equipped with a charging management system that autonomously monitors energy levels, selects appropriate charging stations, and manages recharging operations without driver intervention. This self-service capability allows the vehicle to maintain optimal energy levels with a smaller battery by automatically utilizing available charging infrastructure along its operational route.
3Reliability
If the driver manually monitors and manages charging needs, then the vehicle can maintain optimal energy levels, but the driver burden and operational complexity increase
Solution Approach 1:
The charging management system performs autonomous energy monitoring, charging station selection, and charging coordination without requiring driver intervention. The control unit independently assesses energy requirements, compares them with present charge levels, and automatically manages the recharging process, significantly reducing driver workload while maintaining reliable energy management.
Solution Approach 2:
The manual driver action of monitoring and managing charging is replaced by an automated electronic control system. The control unit uses computational algorithms to estimate energy requirements, process charging station data, and execute charging decisions, substituting human cognitive and manual operations with automated electronic decision-making.
4Reliability
If the vehicle frequently interrupts workflow to recharge, then the energy storage unit can be kept at optimal charge levels, but the overall productivity and operational efficiency decrease
Solution Approach 1:
The system estimates total energy requirements in advance and compares them with present charge levels before tasks begin. This preliminary planning allows the vehicle to complete tasks continuously when energy is sufficient, avoiding unnecessary charging interruptions and maintaining high productivity while still optimizing charge levels.
Solution Approach 2:
Real-time monitoring of state of charge against estimated consumption provides feedback that triggers charging actions only when necessary. This feedback-controlled approach ensures charging occurs at optimal moments to maintain reliability without causing unnecessary workflow interruptions that would reduce productivity.
Data Source
AI summary
A charging management method includes estimating via a control unit a total energy requirement to be met by a rechargeable electrical energy storage unit for performing an agricultural task, comparing via the control unit the estimated total energy requirement with a present state of charge of the electrical energy storage unit, and when the comparison is not sufficient to complete the agricultural task, the control unit retrieves charging infrastructure information relating to a geographical position of a plurality of charging stations along a route to be covered during the agricultural task from a data memory, ascertains an intention for a travel interruption of the agricultural working vehicle to be inserted, depending on the application, along the route, and assigns the geographical position of the travel interruption to at least one of the plurality of charging stations and outputs a charging recommendation via a data interface.