Working Machine Battery Management System for Off-Highway Vehicles
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Solution Overview
Problem
Off-highway working machines, such as tractors and construction vehicles, face challenges in managing battery power effectively while operating on steep or uneven terrain, as existing systems fail to optimize battery usage based on real-time and historical data, leading to potential battery depletion during tasks.
Innovation Solution
A battery management system that combines real-time and historical data from various sources, including ambient temperature, terrain, and soil conditions, to adjust operation plans and ensure sufficient battery charge, allowing for notifications and adjustments to the work path or implement settings to prevent battery depletion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the working machine operates on steep or uneven terrain with high power demand, then the productivity and work capability are improved, but the battery charge depletes faster leading to potential power exhaustion
Solution Approach 1:
The system performs preliminary actions by identifying charging opportunities before the battery is depleted. The operation plan logic proactively modifies work paths to include charging stops based on predicted power requirements and available charging locations, preventing power exhaustion before it occurs
Solution Approach 2:
The system dynamically adjusts the operation plan based on real-time battery charge levels and environmental conditions. The work path, work rate, and charging stops are continuously modified to optimize the balance between productivity and battery consumption, allowing the machine to adapt to changing terrain and power availability
2Reliability
If the system continuously monitors and adjusts operation plans based on real-time and historical data, then the battery charge management is optimized, but the system complexity increases
Solution Approach 1:
The system implements feedback mechanisms by continuously monitoring battery charge levels, environmental conditions, and historical power consumption data. This feedback drives automatic adjustments to the operation plan, including modifying work paths and inserting charging stops, thereby optimizing battery management through data-driven decisions
Solution Approach 2:
The operation plan logic autonomously modifies work paths and schedules charging stops without requiring external intervention. The system serves itself by automatically responding to battery charge levels and environmental conditions, reducing the need for complex external control systems
Data Source
AI summary
Embodiments herein relate to a working machine that may include one or more batteries. The working machine may further include logic that is configured to: identify an operation plan to be performed by the working machine in a work area; identify an amount of power required to complete the operation plan; identify an amount of power remaining in the one or more batteries; alter, based on a comparison of the amount of power required to complete the operation plan to the amount of power remaining in the one or more batteries, the operation plan to generate a revised operation plan; and facilitate implementation, by the working machine, of the revised operation plan. Other embodiments may be described and/or claimed.