Vehicle Energy Use Simulation via Real-World Drive Cycle Data
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods fail to accurately simulate fuel usage of vehicles before purchase, leading to mismatched expectations and misleading return-on-investment calculations due to reliance on manufacturer-supplied data and complex simulation tools inaccessible to consumers.
Innovation Solution
A system comprising a network-accessible server, energy modeling tool, data logging tool, and fleet management tool that collects real-world drive cycle data to estimate energy use of vehicles under consideration, providing more accurate energy consumption predictions and return-on-investment analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manufacturer-supplied fuel consumption data is used, then the data is easily accessible and standardized, but the accuracy of fuel consumption prediction is poor due to mismatch with real-world drive cycles
Solution Approach 1:
The patent creates a simplified copy of complex vehicle simulation tools by using pre-built energy consumption functions and drive cycle data libraries. Instead of requiring users to build complex models, the system provides pre-processed simulation results that can be directly applied to predict fuel consumption for specific vehicle models and driving conditions, thereby achieving accurate predictions without the complexity of full simulation software
Solution Approach 2:
The patent introduces an intermediary layer between complex vehicle dynamics and simple fuel consumption predictions. This intermediary consists of pre-processed energy consumption functions and drive cycle data that bridge the gap between detailed vehicle modeling and practical fuel economy estimation, allowing accurate predictions without requiring users to understand or implement complex simulation algorithms
2Measurement precision
If complex simulation software is used, then fuel consumption prediction accuracy is improved, but the software becomes inaccessible to consumers and limited to vehicle manufacturers
Solution Approach 1:
The patent extracts the essential functionality of complex simulation software by separating the core prediction algorithm from the complex user interface and configuration requirements. The energy consumption functions and drive cycle data are extracted as pre-processed, ready-to-use components that can be accessed through simple interfaces, thereby making the predictive capability accessible to consumers while retaining the accuracy of complex simulations
Solution Approach 2:
The patent replaces expensive, complex simulation software with inexpensive, easily accessible prediction tools. By using pre-processed energy consumption functions and drive cycle data libraries, the system provides accurate fuel consumption predictions through simple queries rather than requiring users to invest in and operate complex simulation software, thereby improving accessibility without sacrificing prediction accuracy
3Measurement precision
If real-world drive cycle data is collected, then fuel consumption prediction accuracy is improved, but the data collection and processing complexity increases
Solution Approach 1:
The patent performs preliminary processing of real-world drive cycle data by pre-computing energy consumption functions and storing them in libraries. This preliminary action transforms raw, complex data into pre-processed, ready-to-use functions that can be directly queried for prediction purposes, thereby achieving accurate energy use estimation without requiring users to perform complex data collection and processing tasks
Data Source
Figure 1
Figure 2~3
Figure 4
AI summary
A system, method and computer program for simulating vehicle energy use is provided. The system comprises a server, an energy modeling tool, a data logging tool and a fleet management tool. The energy modeling tool is linked to a server and generates energy consumption data that provides an energy consumption function of a vehicle under consideration. The data logging tool is linked to test vehicles and collects drive cycle data from real-world driving conditions. The data logging tool then communicates the drive cycle data to the server over a network. The fleet management tool is also linked to the server and combines the energy consumption data with the drive cycle data to estimate the energy use of a vehicle under consideration.