EV Data Offloading Scheduling for Route-Aware Network Constraints
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Solution Overview
Problem
Current data management methods in electric vehicles lack optimization for data offloading during travel based on network capability awareness, leading to inefficiencies and data congestion.
Innovation Solution
A method for optimizing data offloading in electric vehicles involves estimating data categories (real-time, near real-time, and non-real-time) and determining offloading stops based on network access device information, using a combination of cellular and WiFi connectivity to manage data transfer efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data is continuously collected and transmitted without categorization, then data completeness is maintained, but network congestion and transmission costs increase
Solution Approach 1:
The patent segments data into three categories (real-time, near real-time, and non-real-time) based on urgency and transmission requirements. This segmentation enables selective offloading strategies where critical data is transmitted immediately while less critical data is deferred, resolving the contradiction between maintaining data completeness and improving offloading efficiency.
Solution Approach 2:
The system dynamically adjusts transmission parameters based on data category and network conditions. By changing transmission timing and priority parameters according to data urgency levels, the system optimizes the balance between data completeness and transmission efficiency, reducing network congestion without losing critical information.
2Productivity
If data offloading stops are frequently scheduled, then data transmission efficiency improves, but vehicle travel time increases
Solution Approach 1:
The system performs preliminary data categorization and offloading stop scheduling before the vehicle reaches the destination. By pre-determining optimal offloading timing based on predicted data generation patterns and network conditions, the system minimizes actual stopping time while maximizing offloading efficiency, reducing the trade-off between transmission efficiency and travel time.
Solution Approach 2:
The offloading stop schedule is made dynamic and adaptable rather than fixed. The system continuously monitors actual data generation rates and network conditions, adjusting stop timing and duration in real-time. This dynamic approach allows the system to optimize the balance between offloading efficiency and travel time based on actual conditions rather than following a rigid schedule.
3Reliability
If multiple network access points are used, then connectivity reliability improves, but system complexity increases
Solution Approach 1:
The patent introduces a network selection module as an intermediary that manages communication between the vehicle and multiple network access points. This intermediary component automatically handles network registration, data routing, and connectivity monitoring, improving connectivity reliability while containing the complexity within a dedicated management function rather than dispersing it throughout the system.
Solution Approach 2:
The network management system is designed with multi-functional capabilities that handle multiple network types (cellular, WiFi, satellite) through a unified architecture. By making the network management function universal rather than creating separate specialized systems for each network type, the patent improves connectivity reliability across diverse networks while minimizing the overall complexity increase.
Data Source
AI summary
Methods and systems for optimizing data offloading in electric vehicles are described. A method includes estimating an amount of data that can be collected and generated for a route generated for a destination entered into the electric vehicle, categorizing, by a data offloading device in an electric vehicle, the estimated data into real-time, near real-time, and non-real-time data categories, determining one or more offloading stop and time based on the categorized estimated data and service provider access device information for the route; collecting real data generated by and for the electric vehicle as the electric vehicle traverses the route; categorizing the real data into the real-time, the near real-time, and the non-real-time data categories; and updating the one or more offloading stop and time based on the categorized real data and updated service provider access device information for the route.