Currently, network technology is a new technology in the field of automotive electronics. It not only solves the problems of complex wiring and increased wiring harnesses in automotive electronics, but its communication and resource sharing capabilities also form a foundation for the application of new electronic and computer technologies in vehicles, supporting the vehicle's information and control system. Automotive electronic networks can be functionally divided into control-oriented networks (CON) and information transmission-oriented networks (ION). Based on network information transmission speed, the Society of Automotive Engineers (SAE) classifies networks into three categories: A, B, and C. Category A is a low-speed network with a baud rate below 9600 bps; Category B has a baud rate below 125 kbps; and Category C has a baud rate above 125 kbps. Wheel speed (i.e., the linear speed of the wheel rotating around its axle) sensor signals can be shared by the engine control module, anti-lock braking system (ABS) control module, and instrument cluster control module, enabling the ABS control module and engine control module to work together during braking to achieve optimal braking performance. While developed countries widely use ABS systems, wheel speed signal processing is typically handled through dedicated circuits and chips integrated into the ABS system's electronic control unit (ECU) in both hardware and software for protection. Domestic wheel speed signal processing often suffers from an excessively high threshold for wheel speed recognition (wheel speed cannot be accurately measured when the vehicle speed is below 10 km/h). This paper utilizes a self-developed rotary drum wheel speed sensor test bench to conduct experiments. Based on the signal characteristics generated by the wheel speed sensor, a CAN bus-based automotive wheel speed sensor signal processing circuit was designed, and a microcontroller was used to acquire and quantize the signal. Results show that the designed wheel speed sensor system has advantages such as a low wheel speed measurement threshold (up to 3 km/h), reliable operation, and strong anti-interference capabilities. Furthermore, it can serve as a measurement point in a CAN bus local area network, enabling the digital and networked transmission of sensor signals. Because magnetoelectric sensors are stable and reliable, and virtually unaffected by environmental factors such as temperature and dust, variable reluctance electromagnetic sensors are widely used in automotive wheel speed sensors. A variable reluctance wheel speed sensor consists of a stator and a rotor. The stator consists of two parts: an induction coil and a magnetic head (a magnetic pole composed of permanent magnets). The rotor can be either a gear or a ring gear. The gear rotor is shown in Figure 1(a). The magnetic head is fixed on the magnetic pole support, the support is fixed on the long shaft, the ring gear is connected to the hub and brake hub, and the long shaft passes through the wheel and engages with the internal bearing, as shown in Figure 1(b). The rotor speed is proportional to the angular velocity of the wheel. The drum drives the wheel to rotate, and the tooth tip and the gap between the teeth of the sensor rotor alternately approach and leave the magnetic pole, causing the magnetic field in the stator induction coil to change periodically, inducing an AC sine wave signal in the coil. The test bench is used to make the wheel run under various working conditions and to measure the output signal of the sensor. The experimental results show that the signal generated by the variable reluctance wheel speed sensor has the following characteristics: (1) The signal generated by the sensor is a sine wave signal with a near-zero mean; (2) The amplitude of the sine wave signal is affected by the air gap interval (the air gap between the magnetic head and the ring gear, which is generally about 1.0 mm for the most ideal) and the wheel speed. The smaller the air gap, the higher the wheel speed, and the larger the amplitude of the sine wave signal; (3) The frequency of the sine wave signal is affected by the number of teeth of the gear ring and the wheel speed, which is the number of teeth passing through the magnetic head coil per second, that is, equal to the number of teeth of the gear ring multiplied by the wheel speed per second. The signal generated by the variable reluctance wheel speed sensor is shown in Figure 2. The experiment simulated the front wheel of the BJ212 model, and the speed of the drum was used to simulate the vehicle speed. When the drum speed was controlled at 3km/h, the amplitude of the sine wave signal generated by the 88-tooth sensor was about 1V, and its frequency was 31Hz; when the drum speed was controlled at 100km/h, the amplitude of the sine wave signal generated by the sensor was about 7V, and its frequency was 1037Hz. Due to the burrs generated by gear processing and the influence of other environmental factors, the actual signal is a certain frequency component interference signal superimposed on the above signal, as shown in Figure 2(b). Wheel speed signal detection Each sine wave signal output by the wheel speed sensor is conditioned and shaped to generate a square wave signal. The subsequent circuit can process the square wave signal in the following ways: (1) Directly send it to the T0 counter of the microcontroller and use T1 as a timer. Read the value of T0 during each T1 time interval and calculate the wheel speed; (2) First convert the square wave signal to F/V, and then convert it to A/D by the microcontroller to obtain the wheel speed; (3) Send the square wave signal to the external interrupt/INT0 pin of the microcontroller, set it to edge-triggered mode, use T1 as a timer to measure the period of the square wave signal, and calculate the wheel speed. The first method has a large error in the wheel speed measured at low speeds. Assuming a constant wheel speed, the value of T0 is read once every T1 time interval. The values ​​read within T1i and T1i+1 times sometimes differ by 1 due to the positional relationship between the magnetic head and the tooth tip during reading. At lower wheel speeds, the value of T0 within the T1 time interval is smaller, resulting in a larger relative error and an excessively high threshold for wheel speed recognition. The second method improves measurement accuracy at low speeds but increases the cost of hardware F/V and A/D conversion chips. The third method effectively improves measurement accuracy at low speeds without increasing hardware costs. Wheel Speed ​​Sensor System Hardware The wheel speed sensor system hardware is based on an 80C31 microcontroller (externally expanded with 8k RAM and 8k EPROM). Peripheral circuits include signal processing circuits, bus control, and bus interface circuits. Its block diagram is shown in Figure 3. The signal generated by the wheel speed sensor is filtered, shaped, and opto-isolated before being sent to the /INT0 input pin of the 80C31. T1 is used as a timer to periodically measure the pulse signal. The SJA1000 and 82C250 microcontrollers form the control and interface circuit for the CAN bus. In the design of the wheel speed sensor, anti-interference and stability were fully considered. The microcontroller's input/output terminals are opto-isolated, and a watchdog timer (MAX813) is used for timeout reset to ensure reliable system operation. Signal Processing Circuit Based on the characteristics of the wheel speed sensor signal, the processing circuit consists of a limiting circuit, a filtering circuit, and a comparison and shaping circuit, as shown in Figure 4. The limiting circuit limits the amplitude of the positive half-cycle of the wheel speed sensor output signal Vi to below 5V, and the negative half-cycle to -0.6V. The filtering circuit is designed as an active low-pass filter with feedback, and its cutoff frequency is 2075Hz (designed based on a maximum vehicle speed of 200km/h, the frequency corresponding to the sensor output signal), with Q=0.707 selected. A certain comparison voltage is set in the comparison and shaping circuit, which is compared with the filter output signal to output a square wave signal. The LM311N outputs a 10V square wave, which, after being divided by resistors R5 and R6, yields a 5V square wave signal that is sent to the opto-isolator. Bus Communication Circuit The bus interface circuit includes the sensor-CAN bus interface and the instrument panel node-CAN bus interface. Data, control commands, and status information are transmitted between sensors and nodes through the bus interface circuit. Using the bus interface facilitates the formation of a bus-based vehicle local area network topology. It features simple structure, low cost, and high reliability. The sensor-CAN bus interface is based on the CAN controller SJA1000, using an 82C250 to implement the interface between the sensor and the physical bus. All functions of the CAN bus physical layer and data link layer are performed by the communication controller SJA1000. It has two operating modes: BasicCAN (82C200 compatible mode) and PeliCAN (extended features), adopts a multi-master structure, and has interfaces for connecting to various types of microprocessors. The SJA1000's pin functions and electrical characteristics are fully compatible with the 82C200, but it offers enhanced error diagnosis and handling capabilities. It features a programmable clock output, programmable transmission rates (up to 1 Mbps), programmable output driver configuration, a configurable bus interface, and bus access priorities defined by identification codes. The controller is easy to use, inexpensive, and operates over a wide temperature range (-40 to 125°C), making it particularly suitable for automotive and industrial environments. The 82C250, serving as the interface between the CAN bus controller and the physical bus, is designed for high-speed automotive data transmission (up to 1 Mbps). It provides differential reception to the CAN controller and differential transmission to the bus, fully compliant with the ISO11898 standard. In dynamic environments, it exhibits transient, radio frequency, and electromagnetic interference immunity, and its internal current-limiting circuitry protects the transmission output stage from short circuits. The chip features a design that allows it to operate in three modes through the input level of the Rs (pin 8): (1) high-speed mode (Vrs < 0.3Vcc); (2) slope mode (0.4Vccrs < 0.6Vcc); and (3) standby mode (Vrs > 0.75Vcc). When the chip operates in high-speed mode, the transmit output transistors are switched on and off as quickly and simply as possible, without measuring or limiting the rise and fall slopes. Shielded cables are used to avoid radio frequency interference. When the chip operates in slope mode, the bus can use unshielded twisted-pair or parallel lines. The limits on the rise and fall slopes depend on the connection resistance value from the Rs pin to ground and are proportional to the current of the Rs pin. The signal levels of the SJA1000 and 82C250 are TTL compatible and can be directly interfaced. However, to improve reliability and anti-interference performance, they are opto-isolated in the design of smart sensors. The RD, WR, ALE, and INT pins of the SJA1000 are connected to the RD, WR, ALE, and INT0 pins of the 80C31, respectively. The P0.0 to P0.7 pins of the 80C31 microcontroller interface with the AD0 to AD7 pins of the SJA1000. Both the 80C31 and SJA1000 are powered by a common 5V power supply. A sustaining potential of approximately 0.5Vcc is provided to the RX1 pin of the SJA1000. A 120Ω matching resistor is connected in parallel between the CANH and CANL pins of the 82C250 before connecting to the physical bus. The Rs pin is grounded, selecting high-speed mode. Shielded cable is used as the transmission medium to improve the anti-interference capability of the bus interface. Experimental Results The signal processing circuit was tested first. A sine wave generated by an XD5-1 signal generator simulated the sensor signal input circuit, and the input and output waveforms were observed using a dual-trace oscilloscope. When the input signal peak value is above 0.6V, the circuit outputs a square wave with no signal loss. Similarly, no signal loss was observed when the frequency ranged from 20 to 2075Hz. When the signal value was below 0.6V, no square wave was output, meaning noise below 0.6V could not enter the microcomputer system. The threshold value of the minimum signal can be changed by adjusting the resistance values ​​of R2 and R3 in the circuit. The sensor signal was tested on a drum sensor test bench. The test results are shown in Table 1. The radius of the front wheel of the BJ212 model is 0.375m, and the gear ring of the magnetic induction sensor has 88 teeth. The difference between the speed measurement system display value and the speedometer reading in the table is due to the speedometer error. The vehicle speed ranges from 3 to 200 km/h, corresponding to frequencies from 31 to 2075 Hz, and the designed speed measurement system completely covers this speed range. When tested with a non-contact infrared speedometer, the error was within 0.3%, proving the rationality of the sensor and signal processing circuit. Information transmission test with the instrument panel node: the sensor speed measurement system and the instrument panel node's received and transmitted signals are consistent; the data format of the transmitted and received signals is consistent with the set 11-bit data format. Conclusion The CAN bus-based wheel speed sensor fully leverages the potential of magnetic induction sensors, offering advantages such as a low threshold for vehicle speed recognition (3 km/h), high measurement accuracy, practicality, strong anti-interference capabilities, and reliable operation. It is suitable for use in automotive motion environments and easily networked with other measurement and control nodes to achieve networked transmission of sensor data.