EV Operation Planning With Battery Deviation Re-Planning
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Solution Overview
Problem
Existing systems fail to account for unexpected power depletion in electric vehicles, particularly during logistics operations, leading to inefficiencies and additional burdens when power depletion occurs in delivery vehicles.
Innovation Solution
An operation management system and method that includes an operation planning unit, re-planning necessity determination unit, and influence range detection unit to create, compare, and re-plan operation plans for electric vehicles based on actual and predicted battery levels, weather, traffic, and other conditions, ensuring efficient vehicle dispatch and reducing power depletion risks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If electric vehicles are used for logistics delivery operations, then delivery efficiency is improved, but power depletion risk increases due to unexpected energy consumption from heating, air conditioning, and other auxiliary systems
Solution Approach 1:
The operation management server performs preliminary power consumption prediction and operation plan re-planning before power depletion occurs. When a vehicle is predicted to experience power depletion, the system proactively creates alternative operation plans and notifies relevant parties in advance, preventing delivery disruptions rather than reacting after depletion occurs.
Solution Approach 2:
The system continuously monitors actual power consumption and compares it with predicted values, using this feedback to dynamically adjust operation plans. The re-planning necessity determination unit compares actual measured values with predicted values to determine whether re-planning is required, creating a closed-loop control system that adapts to real-time conditions.
2Productivity
If operation plans are re-planned for vehicles experiencing power depletion, then overall operation efficiency is improved, but system complexity increases due to coordination across multiple vehicles and stakeholders
Solution Approach 1:
The operation management server performs multiple functions including power consumption prediction, re-planning necessity determination, influence range detection, and operation plan re-planning within a single integrated system. This multi-functional approach consolidates complexity into one central system rather than requiring separate systems for each function.
Solution Approach 2:
The system divides the complex re-planning process into distinct functional modules: prediction unit, re-planning necessity determination unit, influence range detection unit, and operation plan re-planning unit. Each module handles a specific aspect of the problem, making the overall system more manageable and easier to implement.
3Measurement precision
If the system monitors and compares actual vs predicted battery levels for all vehicles, then power depletion prediction accuracy is improved, but information processing load increases
Solution Approach 1:
The system applies different levels of monitoring and analysis to different vehicles based on their specific conditions and risk profiles. The influence range detection unit identifies which vehicles are most affected by power depletion issues and focuses detailed analysis on those cases, rather than uniformly processing all vehicles with the same level of detail.
Data Source
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AI summary
An operation management system for managing an operation of a plurality of electric vehicles includes: an operation planning unit configured to create an operation plan for the electric vehicles based on a precondition; a re-planning necessity determination unit configured to compare an actual measured value of a remaining battery level with a predicted value of the remaining battery level in the operation plan for an electric vehicle traveling according to the operation plan, and determine whether it is required to re-plan the operation plan; and an influence range detection unit configured to compare a value of the precondition when the operation plan is created with an actual measured value of a corresponding condition for the operation plan determined to require re-planning, and specify a condition with a discrepancy as a factor of the re-planning. The operation planning unit re-plans an unexecuted operation plan influenced by the condition specified as the factor. Therefore, efficiency of the operation of the plurality of electric vehicles can be improved.