Vehicle Software Updating Differential Combination
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional differential updating methods are inefficient when updating software for multiple vehicle controllers, as they do not effectively optimize the size of updating data due to the similarity in software architectures and functions among controllers.
Innovation Solution
A software updating system and method that involves acquiring differential data between original and updated images for each controller, generating low-ranking differential data, and determining optimal differential combinations to minimize the size of updating data, allowing for simultaneous updates across multiple controllers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If a general differential updating method is applied to update software of multiple controllers, then the updating process can be performed, but the size of updating data cannot be optimized due to lack of consideration for software similarity among controllers
Solution Approach 1:
The patent merges the updating processes of multiple controllers by identifying and extracting common differential data across controllers with similar software architectures. Instead of treating each controller independently, the system combines updating operations at the vehicle level, extracting differentials from grouped controllers and applying them systematically to reduce overall data transmission requirements.
Solution Approach 2:
The patent creates a universal updating approach that works across multiple controller types by establishing a multi-level differential extraction system. The system can handle both individual controller updates and grouped updates, making the updating method adaptable to various controller configurations and software similarities, thereby achieving multi-functional updating capability.
2Reliability
If differential data is extracted for each controller independently, then the updating can be performed accurately, but the data transmission time and cost increase
Solution Approach 1:
The patent combines differential extraction operations across multiple controllers by identifying software similarities and grouping controllers accordingly. The system extracts common differentials from grouped controllers simultaneously rather than sequentially, reducing total data transmission time while maintaining update accuracy through systematic application of extracted differentials to each target controller.
3Ease of manufacture
If the entire controller firmware is transmitted for updating, then the updating can be performed without considering software similarity, but the size of updating data becomes unnecessarily large
Solution Approach 1:
The patent extracts only the necessary differential portions from controller firmware by comparing software versions and identifying changes. Instead of transmitting entire firmware images, the system extracts and transmits only the relevant differential data that needs to be applied to update controllers, significantly reducing data size while maintaining update effectiveness.
Solution Approach 2:
The patent segments the firmware updating process into differential extraction, differential transmission, and differential application stages. By dividing the updating process into these segments and further segmenting controllers into groups based on software similarity, the system efficiently manages data transmission and applies updates selectively to reduce overall data requirements.
Data Source
AI summary
A software updating system based on differential updating for reducing the size of updating data and a method of controlling the same are provided. The method includes acquiring differential data between an original image and an updating image for each of a plurality of updating target controllers included in a vehicle. Then low-ranking differential data is acquired in at least one stage between differential data for each of the plurality of updating target controllers and a plurality of differential combinations are generated for all of the plurality of updating target controllers. An optimum combination of the plurality of differential combinations is then determined and updating data is generated depending to the optimum combination.