BEV Power Forecasting for Refrigeration Load and Range Planning
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Solution Overview
Problem
Battery Electrical Vehicles (BEVs) have limited autonomy compared to thermal engines, and there is a need to accurately forecast energy consumption for refrigeration units to optimize daily operations, including estimating the impact of temperature differences on battery life and refrigeration capacity.
Innovation Solution
A method and system that utilize real-time vehicle data, including state of charge, load conditions, and weather forecasts, to calculate energy consumption and travel distance, incorporating a machine learning model to analyze user driving patterns and display updated travel distances on a human-machine interface, while also estimating the impact of temperature differences on energy consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If real-time monitoring and forecasting systems are implemented in BEVs, then energy management precision is improved, but device complexity increases
Solution Approach 1:
The ECU is designed to perform multiple functions: it monitors vehicle operations, forecasts energy consumption, receives delivery information, calculates travel distances, and communicates with external systems. By making the ECU a multi-functional universal device, the patent improves energy management precision without adding separate dedicated systems for each function, thus limiting the increase in device complexity.
Solution Approach 2:
The system uses the BEV's existing sensors, communication interfaces, and processing capabilities to perform energy forecasting and monitoring. Rather than adding external monitoring equipment, the patent leverages the vehicle's own resources (ECU, existing sensors, onboard communication) to provide self-service energy management, reducing the need for additional complex external systems.
2Measurement precision
If comprehensive real-time data collection is performed, then energy consumption calculation accuracy is improved, but loss of time for data processing increases
Solution Approach 1:
The system receives and stores delivery information in advance before the actual deliveries occur. By having delivery data预先 available, the ECU can perform energy consumption calculations and travel distance forecasts without waiting for real-time data collection during deliveries, thus improving calculation accuracy while minimizing data processing time delays.
Solution Approach 2:
The ECU continuously monitors vehicle operations and continuously updates energy consumption forecasts based on real-time data. This continuous processing allows the system to maintain accurate energy calculations without periodic large-batch processing that would cause time delays, enabling real-time energy management with minimal processing interruptions.
3Reliability
If temperature difference impact estimation is included, then refrigeration capacity management is improved, but device complexity increases
Solution Approach 1:
The temperature difference impact estimation is merged into the existing energy consumption calculation framework. Rather than creating a separate refrigeration management system, the patent integrates temperature-based refrigeration load estimation with the overall energy consumption model, allowing improved refrigeration capacity management through the same ECU that handles general energy management, thus limiting additional complexity.
Data Source
AI summary
A method for managing power consumption in a BEV includes obtaining real time vehicle data via an ECU of the BEV and receiving information regarding deliveries that are planned by a user for a specific day based on a user input or data acquisition from a remote database. The method further includes determining consumption of energy for completion of the deliveries on the specific day based on the obtained real time vehicle data and the received information and then calculating a distance that can be traveled by the BEV based on the determined consumption of energy. The method further includes determining a temperature difference between an internal temperature of a TRU of the BEV and an external temperature outside the TRU in real time, estimating an impact of the determined temperature difference on the determined consumption of energy, and thereafter displaying the results of the estimation on an HMI.