Vehicle Battery Charge Estimation During Offline Charging
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Solution Overview
Problem
Commercial vehicle fleets face challenges in determining fuel and energy efficiency due to the complexity and diversity of vehicle activities, making it difficult to collect and analyze data for improving usage efficiency.
Innovation Solution
A vehicle gateway device is attached to each vehicle to gather and aggregate data, which is then transmitted to a management server for analysis, allowing for the determination of fuel/energy efficiencies, safety scores, and other metrics through interactive graphical user interfaces.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If vehicle diagnostic data is collected at high frequency in real-time, then data completeness and measurement precision are improved, but data volume and processing complexity increase significantly
Solution Approach 1:
The patent segments the continuous high-frequency vehicle diagnostic data into discrete time intervals (e.g., 1-second windows). Within each interval, multiple data samples are collected and processed separately, transforming a continuous complex data stream into manageable discrete units that can be handled more efficiently.
Solution Approach 2:
The system performs preliminary actions by pre-defining time intervals and aggregation rules before data collection begins. This allows the system to pre-allocate processing resources and establish data structures in advance, reducing the computational burden during actual real-time processing.
2Loss of information
If comprehensive vehicle activity data is collected for all vehicles in the fleet, then fuel and energy efficiency analysis capability is improved, but data collection and transmission burden increase
Solution Approach 1:
The patent extracts only the essential data elements needed for fuel and energy efficiency analysis from the comprehensive vehicle diagnostic data. By identifying and extracting only the relevant parameters (such as speed, acceleration, route information, and temporal data), the system eliminates unnecessary data while preserving the information critical for efficiency calculations.
Solution Approach 2:
The system applies local quality by collecting different types and amounts of data for different vehicles based on their specific operational characteristics and routes. Rather than uniformly collecting all possible data from every vehicle, the system tailors data collection to the local needs of each vehicle's operational context.
3Measurement precision
If detailed vehicle metric data is aggregated and analyzed, then fuel/energy efficiency determination accuracy is improved, but computational resources and processing time increase
Solution Approach 1:
The patent implements periodic action by analyzing vehicle metric data at regular time intervals rather than continuously processing every data point. The system collects data continuously but performs aggregation and analysis operations periodically at predefined intervals, reducing computational load while maintaining measurement accuracy through sufficient sampling frequency.
Data Source
AI summary
A system receives historical vehicle battery data from a gateway device connected to a vehicle. Some vehicles with plug-in rechargeable batteries recommend/require that the vehicle computer be turned off when recharging. Thus, obtaining a current state of charge while a vehicle is charging can be difficult because the vehicle computer can be off. While the vehicle/gateway device is unable to transmit current battery data, the systems estimate a battery charge from the historical data.