Introduction 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 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 magnetic head is fixed on a magnetic pole support, which is fixed on a long shaft. The ring gear is connected as a whole through the wheel hub and brake hub. The long shaft passes through the wheel and engages with the internal bearing. The rotational speed of the rotor is proportional to the angular velocity of the wheel. The drum drives the wheel to rotate. The tooth tips and gaps between the teeth of the sensor rotor alternately approach and leave the magnetic poles, 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 around 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 experiment simulates the front wheel of the BJ212 model, and the speed of the drum is used to simulate the vehicle speed. When the drum speed is controlled at 3km/h, the amplitude of the sine wave signal generated by the 88-tooth sensor is about 1V, and its frequency is 31Hz; when the drum speed is controlled at 100km/h, the amplitude of the sine wave signal generated by the sensor is about 7V, and its frequency is 1037Hz. Due to the burrs generated by gear processing and other environmental factors, the actual signal is a certain frequency component interference signal superimposed on the above signal. Detection of wheel speed signal 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. (1) Read the value of T0 during each T1 time interval and calculate the wheel speed; (2) Convert the square wave signal to F/V first, 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 square wave signal periodically, and calculate the wheel speed. The first method has a large error in the wheel speed measured at low speeds. Assuming the wheel speed is constant, the value of T0 is read once during each T1 time interval. The values ​​read during T1i and T1i+1 time intervals may differ by 1 due to the position relationship between the magnetic head and the tooth tip during reading. When the wheel speed is low, the value of T0 during the T1 time interval is small, resulting in a relatively large error and an excessively high threshold value for wheel speed recognition. The second method can improve the measurement accuracy at low speeds, but increases the cost of hardware F/V and A/D conversion chips. The third method can effectively improve the 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 (with external expansion of 8k RAM and 8k EPROM). Peripheral circuits include signal processing circuits, bus control circuits, and bus interface circuits. 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 measure the period of the pulse signal. SJA1000 and 82C250 form the control and interface circuits with the CAN bus. In the design of the wheel speed sensor, its anti-interference and stability were fully considered. The microcontroller's input/output terminals are all 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. The limiting circuit limits the amplitude of the wheel speed sensor output signal Vi to below 5V during the positive half-cycle and to -0.6V during the negative half-cycle. 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 shaping circuit, which is compared with the filter output signal to output a square wave signal. The amplitude of the square wave output by the LM311N is 10V, which is divided by R5 and R6 to obtain a 5V square wave signal, which is then 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 the sensors and nodes through the bus interface circuit. Using the bus interface, a bus-type vehicle local area network topology can be easily formed. It features simple structure, low cost, and high reliability. The sensor-CAN bus interface is based on the CAN controller SJA1000, and the interface between the sensor and the physical bus is implemented through the 82C250. All functions of the CAN bus physical layer and data link layer are performed by the communication controller SJA1000. It features two operating modes: BasicCAN (82C200 compatible mode) and PeliCAN (extended features), employs a multi-master architecture, 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 1Mbps), 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 within a wide temperature range (-40～125℃), making it particularly suitable for automotive and industrial environments. The 82C250, as the interface between the CAN bus controller and the physical bus, is designed for high-speed information transmission in automotive applications (up to 1Mbps). It provides differential reception to the CAN controller and differential transmission capabilities to the bus, and is fully compatible with the ISO11898 standard. In motion environments, it has transient resistance, radio frequency resistance, and electromagnetic interference resistance. The internal current limiting circuit has the function of protecting the transmission output stage when the circuit is short-circuited. The chip features three operating modes through the design of the input level of the Rs (8) pin: (1) high-speed mode (Vrs < 0.3Vcc); (2) slope mode (0.4Vcc < 0.75Vcc). When the chip operates in high-speed mode, the transmit output transistor turns on and off as quickly and simply as possible, without measuring and 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 limit of the rise and fall slopes depends on the connection resistance value from the Rs pin to ground and is proportional to the current of the Rs pin. The signal levels of SJA1000 and 82C250 are TTL compatible and can be directly interfaced. However, in order to improve reliability and anti-interference performance, they are opto-isolated in the design of smart sensors. The SJA1000's RD, WR, ALE, and INT pins are connected to the RD, WR, ALE, and INT0 pins of the 80C31, respectively. The P0.0 to P0.7 pins of the 80C31 interface with the AD0 to AD7 pins of the SJA1000. Both the 80C31 and SJA1000 are powered by a unified 5V power supply. A sustaining potential of approximately 0.5Vcc is provided to the SJA1000's RX1 pin. 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 bus interface's anti-interference capability. 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 was above 0.6V, the circuit output a square wave with no signal loss. Similarly, no signal loss was observed during the test from 20 to 2075Hz. When the signal is less than 0.6V, there is no square wave output, meaning noise below 0.6V cannot 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 radius of the front wheel of the BJ212 model is 0.375m, and the tooth ring of the magnetic induction sensor has 88 teeth. The difference between the speed measurement system display value and the speedometer reading is due to the speedometer error. The vehicle speed ranges from 3 to 200km/h, corresponding to frequencies from 31 to 2075Hz, and the designed speed measurement system completely covers this speed range. When tested with a non-contact infrared speedometer, the error is 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 receive and transmit 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.