Adaptive Traction Control Gain and Time Constant Adjustment
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Solution Overview
Problem
Existing traction control systems face challenges in maintaining stability and ensuring necessary drive force on varying road surfaces while effectively suppressing slip ratios, particularly due to uncertainties in road conditions and delays in torque transmission.
Innovation Solution
A traction control system that employs model following control with adaptive gain coefficients and time constants, calculated based on real-time slip ratios and friction coefficients, to stabilize torque control and prevent slip, ensuring stable travel and adequate drive force across different road conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If model following control with fixed gain coefficient is used to suppress slip ratio, then slip suppression performance is improved, but control stability deteriorates due to dead time and varying road conditions
Solution Approach 1:
The patent applies dynamics by making the gain coefficient and time constant variable rather than fixed. The control parameters are dynamically adjusted based on real-time road surface friction coefficients and slip ratios, allowing the system to adapt to changing conditions and maintain both stability and effectiveness across varying road surfaces.
Solution Approach 2:
The patent implements parameter changes by modifying the gain coefficient and time constant based on detected road surface conditions. When friction coefficients and slip ratios change, the control parameters are recalculated and adjusted, enabling the system to maintain optimal performance across different road surfaces while preventing instability.
2Speed
If high gain coefficient is used to quickly suppress slip, then slip response speed is improved, but unnecessary torque reduction occurs on high friction surfaces
Solution Approach 1:
The patent applies local quality by tailoring the control strength to the specific road surface conditions. On high friction surfaces, the system reduces the gain coefficient to prevent excessive torque reduction, while on low friction surfaces it increases the gain to ensure rapid slip suppression. This localized adaptation optimizes energy efficiency while maintaining necessary control response.
3Measurement precision
If adaptive control parameters are used to match road conditions, then control accuracy is improved, but system complexity increases
Solution Approach 1:
The patent implements feedback by continuously monitoring road surface friction coefficients and slip ratios, then using this information to adjust control parameters. The feedback loop calculates optimal gain coefficients and time constants based on current conditions, achieving high control accuracy through real-time adaptation without requiring overly complex system architecture.
Data Source
Figure 1
Figure 2~4
Figure 5(A)~5(C)
AI summary
A parameter calculation part (390) calculates an adaptive gain coefficient 'k' for the road surface conditions of the road being traveled upon, on the basis of a frictional coefficient µ and a slip ratio λ sent from an acquisition part (310) and a coefficient 'b' in a storage part (380). Subsequently, the parameter calculation part (390) calculates an adaptive time constant τ by which the stability of traction control can be ensured, on the basis of the gain coefficient 'k' and a coefficient 'a' within the storage part (380). Along with the calculated gain coefficient 'k' being set in a gain multiplication part (370), the calculated time constant τ is set in a filter part (360). According to these settings, model following control is executed by taking, as a reference model, an adhesion model in which driving wheel does not slip. As a result, it is possible to enhance the slip prevention performance while ensuring control stability, and also possible to implement stable traveling while ensuring the required drive force in accordance with the road surface state.