Vehicle Verification Cycle Generation for Multi-Vehicle Boundary Conditions
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Solution Overview
Problem
Existing vehicle development methods fail to account for the variability of adverse conditions on actual roads, such as driving environment, traffic conditions, and vehicle specifications, making it impossible to create a single verification cycle that covers the boundary conditions for multiple vehicles.
Innovation Solution
A method involving clustering and classifying datasets from drive cycles, generating multiple verification cycles using Markov chains, and selecting a representative cycle that best satisfies user-defined criteria, such as worst-case emissions, to create a realistic verification cycle that meets the boundary conditions of a plurality of vehicles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a single verification cycle is created based on historical data and experience, then the verification cycle can be established using existing resources, but it cannot cover the boundary conditions for many vehicles with different specifications and driving conditions
Solution Approach 1:
The patent segments the verification process by dividing vehicles into different groups based on powertrain specifications (engine displacement, maximum output, maximum torque). Instead of creating a single universal verification cycle, multiple verification cycles are generated tailored to each vehicle group, allowing comprehensive coverage of boundary conditions for diverse vehicle types while maintaining manageable complexity through systematic classification
Solution Approach 2:
The patent changes key parameters of the verification cycle based on vehicle specifications. By adjusting the verification cycle parameters according to vehicle group characteristics (different powertrain parameters), the system generates customized verification cycles that accurately reflect the boundary conditions specific to each vehicle type, thereby improving adaptability without requiring a completely separate system for each vehicle
2Adaptability or versatility
If multiple verification cycles are generated for different vehicle groups, then the boundary conditions for many vehicles can be satisfied, but the complexity of generating and managing multiple cycles increases
Solution Approach 1:
The patent implements a dynamic verification cycle generation system that automatically adapts to different vehicle specifications. The system dynamically selects appropriate verification cycles based on vehicle group classification, and can generate new verification cycles as needed rather than requiring manual creation and management of all possible cycles. This dynamic approach reduces management complexity while maintaining comprehensive coverage
Solution Approach 2:
The system incorporates feedback mechanisms where verification results inform future verification cycle generation. By analyzing verification outcomes and boundary condition coverage, the system can identify gaps and generate additional verification cycles针对性地 addressing uncovered scenarios, creating a self-improving system that manages complexity through intelligent adaptation rather than brute-force enumeration
3Measurement precision
If verification cycles are customized for specific vehicle specifications and driving conditions, then the accuracy of boundary condition coverage improves, but the time and resources required to create and execute verifications increase
Solution Approach 1:
The patent performs preliminary classification of vehicles into groups based on powertrain specifications before verification execution. By pre-establishing verification cycles for each vehicle group and pre-processing the classification, the system avoids time-consuming customization during actual verification execution. This preliminary action maintains high accuracy while reducing execution time through systematic preparation
Solution Approach 2:
The system creates verification cycles by copying and adapting templates from similar vehicle groups. Instead of creating entirely new verification cycles for each vehicle, the system copies existing verification cycles and modifies them based on specific vehicle characteristics, significantly reducing the time and resources required while maintaining the precision needed for accurate boundary condition coverage
Data Source
AI summary
The present invention is a verification-cycle generation method for generating a verification cycle for vehicle development, the verification cycle being a realistic one and satisfying boundary conditions for a plurality of vehicles, wherein a plurality of datasets concerning a drive cycle are input, the plurality of datasets are individually clustered and classified into a plurality of data groups, a plurality of verification cycles concerning vehicle development are generated on the basis of the plurality of clustered data groups, each of the plurality of verification cycles is carried out through simulation or with an actual machine, and a representative cycle that best satisfies user-defined criteria is selected from among the plurality of verification cycles.