Battery Data Analysis Scheduling for Storage Load Balancing
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Solution Overview
Problem
The existing methods for analyzing battery data from multiple vehicles face challenges with excessive data load on storage units due to large data volumes, leading to inefficient data analysis and storage.
Innovation Solution
A battery data analysis server system that includes a communication unit, analysis unit, data lake, message queue, scheduler, and storage unit, which independently analyzes and stores battery data from multiple vehicles, adjusting the load on storage units by managing data transmission based on storage capacity and performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If battery data from a plurality of vehicles is collected and analyzed together, then comprehensive battery analysis is achieved, but the time required for data analysis increases excessively
Solution Approach 1:
The patent divides the batch processing of all battery data into individual daily processing tasks for each vehicle. The scheduler generates separate daily data files for each vehicle instead of processing all vehicles' data together in one batch, enabling parallel processing and reducing total analysis time.
Solution Approach 2:
The system performs preliminary filtering to determine which vehicles are moving on each day before generating analysis tasks. By pre-identifying the subset of vehicles that require analysis for each day, the system avoids unnecessary processing of stationary vehicles and reduces overall computation time.
2Quantity of substance
If all battery data is stored at once in the storage unit, then complete data storage is achieved, but excessive load is applied to the storage unit
Solution Approach 1:
The patent segments the storage operation into individual daily data files, one for each vehicle per day. Instead of storing all vehicles' battery data in a single large batch, the system creates separate files that are stored sequentially, distributing the storage load over time and preventing excessive peak load on the storage unit.
Solution Approach 2:
The scheduler operates periodically, processing and storing one day's data for all vehicles before moving to the next day. This periodic batch processing approach spreads the storage load across multiple time intervals rather than concentrating it in a single operation, reducing peak storage unit load.
3Quantity of substance
If battery data is processed in batch mode, then data completeness is maintained, but data analysis efficiency decreases
Solution Approach 1:
The patent segments the batch processing into individual vehicle-level daily processing tasks. Each vehicle's daily battery data is processed independently and stored as a separate file, allowing multiple vehicles' data to be processed in parallel rather than sequentially in a single batch, thereby improving overall analysis efficiency while maintaining data completeness.
Solution Approach 2:
The scheduler acts as an intermediary between data collection and analysis/storage operations. It coordinates the generation of daily data files for each vehicle and manages the timing of storage operations, enabling efficient resource utilization and parallel processing while ensuring all necessary data is captured and stored.
Data Source
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AI summary
A battery data analysis server according to one embodiment disclosed herein includes a first communication unit configured to receive battery data from a plurality of vehicles, an analysis unit configured to determine target vehicles traveling on a target date among the plurality of vehicles, analyze each battery data corresponding to each of the target vehicles, and generate daily data based on the result of the analysis, a data lake configured to store the daily data; a message queue configured to acquire data information including the number of daily data stored in the data lake in real time, a storage unit configured to receive and store at least some of the daily data from the data lake, and a scheduler configured to store the daily data in the storage unit based on the number of daily data being processed by the storage unit and the data information.