Vehicular Micro-Cloud Task Timing Around EV Battery State of Charge
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Solution Overview
Problem
Battery electric vehicles (BEVs) participating in vehicular micro clouds (VMCs) face challenges due to energy consumption discrepancies, which can alter the reported state of charge (SOC) and impact their range, leading to reduced driver confidence and potential exclusion from VMCs, thereby affecting VMC efficacy.
Innovation Solution
A VMC management system that schedules tasks for BEVs based on their battery state of charge (SOC), allowing tasks to be completed immediately if SOC is sufficient or deferred to a later time, such as when connected to a charging station, to maintain battery levels and ensure destination reach.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If BEVs complete VMC tasks immediately, then VMC productivity is improved, but battery energy is depleted reducing range and driver confidence
Solution Approach 1:
The system dynamically adjusts task execution timing based on real-time battery state of charge levels. When SOC is high, tasks are executed immediately to maximize productivity. When SOC drops below thresholds, task execution is deferred or transferred to other vehicles, creating a dynamic balance between productivity and energy conservation
Solution Approach 2:
The system changes operational parameters by monitoring battery SOC and adjusting task execution decisions accordingly. Different SOC thresholds trigger different behaviors: above threshold allows immediate execution, below threshold triggers deferral or transfer, optimizing the trade-off between productivity and energy usage
2Reliability
If BEVs are excluded from VMCs to preserve battery energy, then driver confidence and range are maintained, but VMC functionality is reduced
Solution Approach 1:
Instead of complete exclusion or complete participation, the system implements partial participation where BEVs contribute to VMC tasks selectively based on their energy state. This allows the system to maintain reliability by preserving range while still providing adaptability through selective task participation
Solution Approach 2:
The system continuously monitors battery SOC levels and uses this feedback to adjust VMC participation decisions. This closed-loop control ensures that driver confidence is maintained through proactive energy management while preserving VMC functionality through intelligent task allocation
3Use of energy by moving object
If VMC tasks are deferred to charging stations, then battery energy is preserved, but task completion time increases
Solution Approach 1:
The system performs preliminary assessment of battery SOC levels before task assignment. By predicting future SOC states and planning task execution timing in advance, the system can optimize when tasks are executed versus deferred, reducing unnecessary delays while preserving energy
Solution Approach 2:
The system introduces a task management intermediary that coordinates between VMC tasks and battery state. This intermediary can transfer tasks between vehicles or defer to charging periods, mediating the conflict between immediate task completion and energy conservation
Data Source
AI summary
Systems, methods, and other embodiments described herein relate to the completion of (VMC) tasks by an electric vehicle (EV) based on a battery state of charge (SOC). In one embodiment, a method includes forming a VMC that includes a group of interconnected vehicles that share resources to complete tasks. The group includes an EV. The method also includes scheduling a time when the EV is to complete a planned task of the VMC based on a SOC of a battery of the EV. The method also includes providing data associated with the planned task to the EV.