Vehicle OTA Update Control Using Adaptive Battery Current Profiles
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Solution Overview
Problem
The existing technologies face challenges in accurately determining whether an over-the-air (OTA) update is possible for electronic control units (ECUs) in vehicles, due to variations in vehicle models and options, as well as the decrease in accuracy of current consumption with increasing vehicle age.
Innovation Solution
An apparatus and method that set an initial current consumption for a vehicle, determine if an OTA update is possible based on this consumption and the expected update time, and adjust to an optimal current consumption using measured average consumption during the update, thereby accurately detecting update feasibility regardless of vehicle model or options.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual current consumption settings are used for each vehicle model and option, then accuracy of current consumption determination is improved, but device complexity and ease of operation deteriorate due to the large number of vehicle configurations
Solution Approach 1:
The system performs self-learning by automatically measuring actual current consumption during OTA updates and storing these measurements in a database. The controller automatically selects and adjusts current consumption values based on learned data from the same vehicle model, eliminating the need for manual configuration for each vehicle model and option combination.
Solution Approach 2:
The system implements feedback by continuously measuring actual current consumption during OTA updates, comparing it with expected values, and using this information to refine future predictions. The controller learns from past OTA update performances and adjusts current consumption settings based on real-world data from the same vehicle model.
2Measurement precision
If manual current consumption settings are used for each vehicle model and option, then accuracy of current consumption determination is improved, but ease of operation worsens due to the large number of vehicle configurations
Solution Approach 1:
The system performs self-learning by automatically measuring actual current consumption during OTA updates and storing these measurements in a database. The controller automatically selects and adjusts current consumption values based on learned data from the same vehicle model, eliminating the need for manual configuration for each vehicle model and option combination.
Solution Approach 2:
The controller determines whether an OTA update is possible before actually performing the update by checking battery capacity against expected current consumption. This preliminary assessment prevents unnecessary update attempts and ensures smooth operation by preparing the system in advance.
3Device complexity
If fixed current consumption values are used for OTA updates, then device complexity is reduced, but reliability worsens due to variations in vehicle age and battery capacity
Solution Approach 1:
The system transitions from static fixed current consumption values to dynamic adaptive values. The controller continuously learns actual current consumption patterns specific to each vehicle model and adjusts expectations accordingly. This dynamic adaptation accounts for variations in vehicle age, battery capacity, and operational conditions while maintaining operational simplicity.
Solution Approach 2:
The system changes the parameter of current consumption from fixed predetermined values to learned adaptive values. By storing and utilizing actual measurement data in a database, the system adapts current consumption parameters based on real-world performance of the same vehicle model, improving reliability without increasing complexity.
4Measurement precision
If comprehensive vehicle information is collected for accurate current consumption setting, then measurement precision is improved, but device complexity and loss of information increase due to managing thousands of vehicle configurations
Solution Approach 1:
The system segments the vast vehicle configuration space by using the vehicle model number as the primary classification key. Instead of managing all possible combinations of options and configurations, the system groups vehicles by model and learns common current consumption patterns for each model, significantly reducing information management requirements while maintaining accuracy.
Solution Approach 2:
The system creates a simplified representation by copying and storing only the essential learned current consumption data for each vehicle model in a database. Rather than managing complete detailed configurations of thousands of vehicle variants, the system maintains compact model-specific profiles that capture the essential patterns needed for accurate OTA update determination.
Data Source
AI summary
A device and a method for controlling OTA update of a vehicle, to automatically set an optimal current consumption regardless of a vehicle model and an option for each vehicle model, includes a sensor configured for measuring a current consumption of a battery provided in the vehicle, and a controller that sets an initial current consumption to the vehicle, determines whether the OTA update is possible based on the initial current consumption and an expected over the air (OTA) update time, and determines an optimal current consumption based on the initial current consumption and an average current consumption during the OTA update.