Brake Clamping Control Using Virtual Rotor Temperature Estimation
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Solution Overview
Problem
Existing brake systems face challenges in accurately estimating rotor temperature for adjusting brake clamping force due to the need for complex thermal modeling and the accumulation of errors, which affects reliability and safety.
Innovation Solution
A smart brake system uses a machine learning model trained on historical and simulated vehicle operation data to estimate rotor temperature, incorporating elapsed time since a previous brake event and vehicle specification data, allowing for more accurate adjustment of brake clamping force without complex thermal modeling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If physical temperature sensors are installed on or near the rotors or brake pads, then the rotor temperature can be measured directly and accurately, but the cost of the brake system increases significantly
Solution Approach 1:
The patent creates a virtual copy of the temperature sensor functionality through a thermal model implemented in software. Instead of using physical sensors, the system calculates rotor temperature by simulating heat generation and dissipation processes based on brake usage data, vehicle speed, and environmental conditions. This virtual sensor approach achieves sufficient temperature measurement accuracy without the high cost of physical sensors.
Solution Approach 2:
The patent replaces the mechanical/physical temperature sensing system with a computational thermal modeling system. The physical sensor hardware is substituted by software algorithms that process available vehicle data (brake application force, duration, vehicle speed, ambient temperature) to estimate rotor temperature. This substitution eliminates the need for expensive physical sensors while providing temperature information for brake control.
2Measurement precision
If complex thermal modeling is used to estimate rotor temperature, then temperature estimation accuracy can be improved, but the computational complexity and data requirements increase
Solution Approach 1:
The patent simplifies the thermal modeling by changing the input parameters from requiring detailed physical properties (thermal conductivity, specific heat, density, rotor geometry) to using readily available vehicle operation parameters (brake force, brake duration, vehicle speed, ambient temperature). This parameter transformation reduces modeling complexity while maintaining sufficient accuracy for brake control applications.
Solution Approach 2:
The patent extracts only the essential factors needed for temperature estimation, removing unnecessary complexity from full thermal models. Instead of modeling all heat transfer mechanisms in detail, the system focuses on the dominant factors (brake energy dissipation and ambient cooling) that most significantly affect rotor temperature. This extraction of key factors simplifies the model while preserving accuracy for control purposes.
3Measurement precision
If complex thermal models with detailed physical parameters are used, then temperature estimation accuracy improves, but errors can cumulatively add up throughout a journey
Solution Approach 1:
The patent implements feedback mechanisms where the estimated temperature and brake control decisions are continuously monitored and adjusted. The system uses actual brake performance data and environmental condition changes to refine temperature estimates in real-time, preventing cumulative errors from propagating. This feedback loop ensures reliability by correcting deviations before they significantly impact brake performance.
Solution Approach 2:
The patent performs preliminary calculations of brake energy dissipation and temperature rise before actual braking occurs or during idle periods. By pre-calculating temperature trends based on recent brake usage patterns and environmental conditions, the system prepares accurate temperature estimates in advance, reducing reliance on cumulative calculations that could accumulate errors during active braking events.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system provides reliable and safer brake control by reducing cumulative errors and improving temperature estimation accuracy, enabling finer adjustments to the applied brake clamping force.
Implementation Method 1
brake pads rub against a rotor to slow the vehicle
Implementation Method 2
the temperature of the rotor rises causing the rotor to expand
Implementation Method 3
heat dissipation processes during braking
Data Source
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AI summary
A smart brake system for adjusting a brake clamping force to be applied to brake pads of a vehicle brake in which the brake pads rub against a rotor to slow the vehicle. The system comprises: an interface for receiving vehicle operation data measured by vehicle sensors, a memory device for storing data about a previous brake event, data about a current brake event, and a temperature prediction model, and a controller operatively connected to the interface and the memory device. The controller is configured: to estimate the current temperature of the rotor using the temperature prediction model, and to adjust the brake clamping force applied to the brake pads to compensate for the estimated current temperature. The vehicle operation data include current ambient temperature, current brake clamping force and current vehicle speed. The data about a current brake event include the elapsed time since the current brake event started. The data about a previous brake event include the elapsed time since the previous brake event finished and the duration of the previous brake event. The controller is configured to estimate the current temperature of the rotor from the vehicle operation data, the data about a previous brake event, and the data about a current brake event using the temperature prediction model.