Vehicle Braking Control With Pre-Validated Fuzzy Logic Settings
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Solution Overview
Problem
Existing vehicle braking systems using fuzzy logic lack reliability due to unproven braking instructions, which can lead to safety concerns during real-time braking, as the quality of results from fuzzy logic processes is difficult to guarantee and may require corrections during the braking process.
Innovation Solution
A method involving a three-stage process: generation of candidate braking instructions using a fuzzy logic processor, validation through a decision algorithm that includes regulatory and technical verifications, and implementation of validated instructions on a brake control computer, ensuring secure and reliable braking by simulating various braking situations and utilizing neural networks for self-learning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If fuzzy logic is used to generate braking instructions in real-time, then the braking system can process numerous parameters and adapt to various braking circumstances, but the reliability and safety of the braking instructions cannot be guaranteed
Solution Approach 1:
The patent applies preliminary action by pre-generating candidate braking instructions using fuzzy logic before actual braking events, then validating these instructions through simulations and decision algorithms in advance. This allows the system to prepare multiple pre-validated braking strategies that can be quickly selected during real-time operation, combining the adaptability of fuzzy logic with the reliability of pre-validated instructions.
2Speed
If fuzzy logic processes are used without validation, then the braking system can operate quickly in real-time, but the quality and safety of braking instructions cannot be guaranteed
Solution Approach 1:
The patent segments the braking instruction generation process into distinct phases: candidate generation using fuzzy logic, validation through simulations and decision algorithms, and final selection during real-time operation. This segmentation allows computationally intensive validation to be performed separately from time-critical real-time decision-making, enabling both high-quality validated instructions and fast real-time response.
3Reliability
If braking instructions are validated through simulations and decision algorithms, then the reliability and safety of instructions are improved, but the complexity of the manufacturing process increases
Solution Approach 1:
The patent introduces an intermediary validation system that acts as a mediator between fuzzy logic instruction generation and real-time braking execution. This intermediary layer includes simulation environments and decision algorithms that validate instructions without requiring complex modifications to the real-time braking system, thereby improving reliability while managing overall system complexity.
4Reliability
If multiple validation parameters and simulations are used, then the exhaustiveness of validation is improved, but the time and computational resources required increase
Solution Approach 1:
The patent performs comprehensive validations using multiple parameters and simulations in advance, before actual braking events occur. By completing exhaustive validation work preliminarily, the system ensures high reliability without incurring time delays during critical real-time braking operations, as the validated instructions are ready for immediate deployment.
Data Source
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AI summary
The method, used to manufacture a braking system before its installation in a vehicle, comprises generating braking settings by means of fuzzy logic, involving the influence of multiple parameters (driving styles, sensor signals, model of the vehicle, etc.) simulating particular braking situations (101). The settings thus obtained are then validated (102) by algorithmic processes. Lastly, the validated settings are written (103) to a memory of the computer of the braking system.