Vehicle Performance Comparison via Travel Parameter Distribution
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Solution Overview
Problem
Existing systems lack effective methods to compare and quantify the performance improvements of hybrid vehicles using alternative energy sources with traditional petroleum-based engines, particularly in terms of fuel efficiency and energy conservation across varying operational conditions.
Innovation Solution
A computing device-based method that collects and processes travel parameters for both hybrid and combustion engine vehicles, determining performance metrics and comparison metrics to present fuel savings and operational improvements by analyzing data distributions across speed and acceleration ranges.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If performance data is collected and processed to compare hybrid and combustion engine vehicles, then measurement precision of fuel efficiency improvements is improved, but device complexity increases due to multiple data collection and processing systems
Solution Approach 1:
The computing device is designed to perform multiple functions: collecting travel parameters from multiple vehicle types, processing distribution ranges for different propulsion systems, determining various performance metrics, and generating comparison metrics. This multi-functional approach consolidates what would otherwise require separate systems for each vehicle type and metric calculation.
Solution Approach 2:
The patent combines data collection from hybrid vehicles and combustion engine vehicles into a unified processing framework. The system merges distribution range data from different propulsion systems and vehicle collections, then integrates these datasets to determine both individual vehicle performance metrics and comparative metrics, reducing the need for separate analysis systems.
2Adaptability or versatility
If distribution ranges are standardized across different vehicle types, then adaptability of the comparison system is improved, but loss of information increases due to generalization across diverse operational conditions
Solution Approach 1:
The patent segments the comparison process into distinct distribution ranges for different travel parameters (speed, acceleration, distance). Each parameter is analyzed within its own distribution framework, allowing standardized comparison while preserving the unique characteristics of each operational dimension. The system processes multiple segmented datasets rather than forcing a single generalized model.
Solution Approach 2:
The system applies different processing approaches to different travel parameters based on their specific characteristics. Each distribution range is analyzed with appropriate metrics tailored to that parameter type, preserving local operational details while enabling overall comparison. This allows the system to adapt to diverse operational conditions without complete generalization.
Data Source
AI summary
A computing device-implemented method includes receiving data representative of one or more travel parameters for distribution ranges for a vehicle that includes a first propulsion system, and, receiving data representative of one or more travel parameters for distribution ranges for a vehicle that includes a second propulsion system. The distribution ranges for the vehicle that includes the first propulsion system are equivalent to the distribution ranges for the vehicle that includes the second propulsion system. The method also includes receiving data representative of one or more travel parameters for distribution ranges for a collection of vehicles. The distribution ranges for the collection of vehicles are equivalent to the distribution ranges for the vehicle that includes the second propulsion system.