Tire Transient Response Calculation via Convolution Integrals
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for evaluating tire cornering characteristics, particularly during transient conditions like quick steering or braking, are inadequate as they fail to accurately replicate real-world scenarios, leading to inconsistencies between simulation and actual ride feeling tests, and cannot precisely quantify the dynamic changes in tire behavior.
Innovation Solution
A tire transient response data calculating method using a tire dynamic model that computes convolution integrals of first-order-lag responses to simulate time-series slip angles and forces, allowing for the calculation of transient response data such as lateral forces and self-aligning torques, which are then used to design tires and predict vehicle motion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional tire evaluation methods are used for transient conditions, then the evaluation process is simple, but the accuracy of replicating real-world scenarios deteriorates
Solution Approach 1:
The patent applies dynamics by transitioning from static tire evaluation to dynamic transient response evaluation. The method uses time-varying slip angle inputs and calculates transient response characteristics that capture the dynamic behavior of tires during quick steering and braking conditions, thereby improving accuracy while maintaining manageable model complexity through targeted dynamic analysis.
Solution Approach 2:
The patent changes key parameters by introducing time-varying slip angle inputs and transient response parameters instead of steady-state parameters. This allows the model to capture dynamic tire behavior during transient conditions, improving measurement precision for cornering characteristics without requiring overly complex simulation structures.
2Measurement precision
If steady-state tire models are used, then the model is simple to use, but the ability to quantify dynamic changes in tire behavior deteriorates
Solution Approach 1:
The patent transitions from steady-state to dynamic analysis by implementing transient response calculations that capture time-varying tire behavior. The method maintains ease of operation by building upon existing tire models and adding transient response computation capabilities, making the enhanced dynamic analysis accessible without requiring completely new complex modeling approaches.
Solution Approach 2:
The patent applies preliminary action by pre-defining transient response calculation frameworks and response function forms before actual tire evaluation. This preparation enables straightforward application of the method to various tire conditions while capturing dynamic behavior, balancing quantification accuracy with operational simplicity.
3Reliability
If transient response calculations are implemented, then the accuracy of tire behavior modeling improves, but the computational complexity increases
Solution Approach 1:
The patent manages computational complexity by focusing parameter changes on key transient response characteristics rather than进行全面 dynamic analysis. The method calculates specific transient parameters such as response time constants and damping ratios, improving reliability for cornering predictions while avoiding the need for excessively complex full-field dynamic simulations.
Solution Approach 2:
The patent extracts and focuses on the most critical transient response characteristics needed for cornering prediction, rather than computing all possible dynamic parameters. By selecting and calculating only the essential transient response features, the method improves predictive accuracy for steering stability while keeping computational complexity at manageable levels.
4Reliability
If detailed transient response data is collected, then the steering stability prediction improves, but the data processing requirements increase
Solution Approach 1:
The patent extracts and focuses on the most critical transient response parameters that directly influence steering stability prediction, such as response time constants and damping characteristics. By concentrating on these key parameters rather than processing all available transient data, the method improves prediction accuracy while minimizing data processing time and computational resources required.
Data Source
Figure 1~2
Figure 3
Figure 4A~4C
AI summary
Tire transient response data during cornering with a slip angle is calculated based on a tire dynamic model. A deformation response of a tread part in the tire dynamic is set as a first-order-lag response. The value of the transient response parameter is initialized, to define the first-order-lag response. The time-series data of the transient response of the slip angle between the tread part and a road surface in the tire dynamic model is obtained by computing a convolution integral of the defined response function of the first-order-lag response with a time gradient of the time-series data of the slip angle. A value of a lateral force is calculated by using the tire dynamic model based on the obtained time-series data of the transient response of the slip angle. Accordingly, the transient response data is calculated, and a value of the transient response parameter is obtained.