Dynamic Brake Pad Sampling for Resource Optimization
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Solution Overview
Problem
Existing brake pad state estimation techniques consume significant computational and storage resources due to frequent sensor data sampling, especially when the wear volume or temperature of the brake pad is expected to be low, leading to inefficient resource utilization.
Innovation Solution
A brake pad state estimation device that variably sets the sampling period based on the driving environment, setting it longer when the wear volume or temperature is expected to be low and shorter when it is expected to be high, thereby optimizing resource usage and improving estimation accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a short sampling period is used for continuous sensor data acquisition, then the estimation accuracy of brake pad state is improved, but the consumption of computational resource and storage resource increases significantly
Solution Approach 1:
The sampling period is made dynamic rather than fixed. The control unit adjusts the sampling period based on real-time driving conditions (vehicle speed, brake pressure, duration of brake application). When braking intensity is high, the sampling period shortens to capture critical changes; when braking intensity is low, the sampling period lengthens to reduce resource consumption. This dynamic adaptation resolves the contradiction between measurement precision and resource consumption.
Solution Approach 2:
The system changes the parameter of sampling period based on driving conditions. By calculating the wear volume and temperature based on vehicle speed, brake pressure, and brake duration, the system determines appropriate sampling intervals. This parameter change allows the system to maintain high estimation accuracy during critical braking events while reducing computational and storage resource consumption during normal driving conditions.
2Reliability
If frequent sampling of sensor data is performed, then the reliability of brake pad state estimation is improved, but the productivity of the system decreases due to excessive resource consumption
Solution Approach 1:
The sampling frequency is dynamically adjusted based on the reliability needs of different driving conditions. During high-intensity braking where reliability is critical, frequent sampling is performed. During low-intensity braking or normal driving where reliability requirements are lower, sampling frequency is reduced. This dynamic approach maintains necessary reliability while improving overall system productivity by avoiding unnecessary frequent sampling.
Solution Approach 2:
The system changes the sampling parameter based on calculated braking intensity and predicted brake pad state changes. By using vehicle speed, brake pressure, and duration data to determine when high-reliability estimation is necessary, the system optimizes the balance between reliability and productivity, performing intensive sampling only when truly needed.
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
This approach reduces unnecessary resource consumption while maintaining precise brake pad state estimation, especially in situations where the impact on brake performance is low, and enhances estimation accuracy when the impact is high, ensuring efficient resource allocation and accurate predictions.
Implementation Method 1
a braking force is generated by pressing a brake pad against a brake rotor rotating with a wheel. At this time, the brake pad is worn by friction between the brake pad and the brake rotor
Implementation Method 2
wear characteristics of the brake pad also depend on a temperature of a contact surface (friction part) that comes in contact with the brake rotor. The wear volume tends to be higher as the temperature of the contact surface becomes higher
Data Source
AI summary
A brake pad state estimation device estimates a brake pad state including at least one of a wear volume and a temperature of a brake pad of a vehicle. The brake pad state estimation device acquires sensor detection information including a vehicle speed and a brake pressure, and calculates the brake pad state based on the sensor detection information during braking of the vehicle. The brake pad state estimation device variably sets a sampling period for acquiring the sensor detection information from a sensor according to a driving environment for the vehicle. The sampling period in a case where the wear volume or the temperature of the brake pad is expected to be lower is set to be longer than the sampling period in a case where the wear volume or the temperature of the brake pad is expected to be higher.