The system operates using wheel acceleration signals detected by a TPMS (Tire Pressure Monitoring System). While monitoring tire pressure, the TPMS system uses its built-in acceleration sensor to provide data to the shock absorption detection system. 1. Tire Pressure Monitoring System (TPMS) With the development of integrated circuits and the widespread application of microprocessors, automotive electronics have developed rapidly. Currently, automotive electronics can be broadly categorized as follows: automotive engine electronic control systems, automotive transmission and driving control systems, automotive safety and fault diagnosis systems, automotive information display systems, automotive multiplex buses, automotive environmental protection electronic products, electric vehicles, etc., forming a diverse and independent automotive electronics industry. TPMS is a key automotive safety alarm device in automotive safety and fault diagnosis systems. Its function is to detect and display tire pressure/temperature/acceleration signals in real time, and generate alarm signals when pressure abnormalities occur. TPMS helps improve tire lifespan and vehicle driving safety. A TPMS consists of several wireless digital sensors (lower-level devices) installed inside the tire (tubeless tire) and a host system with wireless transceiver circuitry, as shown in Figure 1. The host computer and each slave computer use a master-slave asynchronous wireless serial communication method. The slave computer is responsible for detecting internal tire information, the host computer displays the information, and generates an alarm signal when pressure, temperature, or other conditions reach dangerous values. Communication between the slave and host computers is accomplished using RF high-frequency signals. The slave detection device is installed at the edge of the tire hub, as shown at point 1 on the wheel edge in Figure 2. It can detect pressure, temperature, and acceleration signals; the host computer display interface is installed on the instrument panel in the driver's cab. 2. Design Purpose and Function of this Method Currently, TPMS is mostly installed in mid-to-high-end cars, many of which have the function of automatically adjusting the characteristics of the shock absorbers according to road conditions. Existing road condition detection methods are based on acceleration sensors installed on the vehicle body. When the car is driving under different road conditions, the control system adjusts the car's shock absorbers accordingly based on the vehicle body vibration, making driving safer and more comfortable. This method works based on the wheel hub edge acceleration signal detected by the TPMS, and uses digital signal processing methods to separate the vibration acceleration value of the wheel caused by road surface fluctuations. The advantage of this method is that the wheel acceleration signal is not filtered by the suspension system, thus providing a more direct and sensitive response to road conditions. Simultaneously, by comparing wheel vibration acceleration with vehicle body vibration acceleration, the performance of the suspension system can be evaluated, and suspension system faults can be located promptly. 3. Theoretical Derivation The sensor is located at the edge of the wheel hub, and its motion acceleration model is as follows: 3.1 Motion Model of a Point on the Wheel Edge When Driving on an Ideal Smooth Road The motion model of a point on the wheel edge when driving on an ideal smooth road is shown in Figure 3. Let the wheel radius be R, and let it roll without slipping along a plane. The velocity of the center point C is Vc = v, and the acceleration is α, both along the y-axis. Let the x-axis and y-axis directions be i and j, respectively. Taking C as the base point, the total acceleration at point P is: The total acceleration at point P is a combination of the linear acceleration of the wheel itself in the forward direction, the centripetal acceleration of the wheel edge point, and the gravitational acceleration of the sensor itself. The reason for considering only the first two terms here is that the gravitational acceleration of the sensor itself is a constant. After the Fourier transform, the energy is concentrated in the region with zero frequency. However, the vibration acceleration signal to be extracted is a rapidly changing quantity, and its energy cannot be concentrated in this region. Discretization: Let the wheel angular velocity be Ω0, the wheel analog angular frequency be Ω=Ω0/2π, and the sampling period be T. Then the digital angular frequency ω0=2πΩT=Ω0T. Assume that v and α are constants in one sampling time. After discretizing equation (2), we get: Therefore, it can be shown that |αP2(n)| has only 3 pulses in its frequency domain expansion. This equation (4) is called the frequency domain expansion equation. These 3 pulses are: From a physical point of view, it is directly related to the wheel speed. 3.2 Extracting vibration acceleration value under road vibration conditions Assuming that the car is driving on a normal road surface, the difficulty of the lower computer detection is that the sampling period T changes with the angular velocity: (2) When the vehicle speed is too low, T is too large, causing the system energy to be wasted. Solution: Divide T into several levels according to the Ω0 value. Assume a criterion for whether the sampling is correct: if the system frequency domain is expanded into a single or three pulses, then the sampling is correct. 3.3 Flowchart The system generates a program that can automatically cycle through the sampling period T. The initial value of T can be set to the T value of the last correct sampling as needed, which can reduce the number of loops. If the sampling is incorrect, the minimum value of T is called again, and so on, until the last value. If all values ​​are incorrect, then the sampling fails. The flowchart is shown in Figure 4. 4 Simulation Analysis 4.1 Simulation Conditions The sampling frequency is 2π times the highest frequency; T value distribution: When v is 0～18 km/h, T＝200 ms; When v is 18～36 km/h, T＝100 ms; When v is 36～72 km/h, T＝50 ms; When v is 72～144 km/h, T＝25 ms. Assume R＝0.3 m, and the vibration acceleration is a random noise signal with an amplitude of 10v. 4.2 Simulation Results (1) Simulation analysis of each v value under uniform speed. Due to space limitations, this paper only uses the minimum and maximum speed values ​​to illustrate the problem, as shown in Figure 5. As can be seen from Figure 5, when the car is traveling at a uniform speed, the vibration acceleration signal extracted by this method is very effective and will not be affected by the car's driving speed. (2) Simulation analysis of each v value when α=0.5 m/s2, as shown in Figure 6. As the car speed increases, the effect will be slightly worse, but it is acceptable for the shock absorption device. 5 Conclusion This method extracts the vibration signal and also separates the wheel rotation signal. If the reliability of the detection can be improved, it can even replace the speed detection sensor of the car ABS system. At present, TPMS obtains power from the wireless power supply device installed on the car fender. When the wheel rotates, the sensor needs to repeatedly approach the charging coil to accumulate enough working energy. Therefore, the measurement is intermittent and cannot replace the ABS speed detection sensor with high real-time requirements at present. To achieve this function, the lower computer must generate power autonomously or other high-efficiency energy transmission methods must be found. Technical solutions in this regard are currently being studied. References [1] Lou Shuntian, Li Bohan. System Analysis and Design Signal Processing Based on Matlab [M]. Xi'an: Xi'an University of Electronic Science and Technology Press, 1998. [2] Zhao Jucai, Shi Junping. Theoretical Mechanics [M]. Xi'an: Shaanxi Science and Technology Press, 1995. [3] Ruan Lourens of Microchip Technology Inc, Curtis Kell of Kell Laboratories. Tire Pressure Monitoring (TPM) System Microchip Technology Inc, 2002. Editor: He Shiping