Based on NZP MK60 microprocessor and integrated sensors (electromagnetic sensor, encoder, nrf24l01, ultrasonic, reed, etc.), the information obtained from the track and the state of the two cars themselves, the completion of overtaking on the track and the smooth and high-speed running of the track also put forward some valuable ideas for the future driverless automobile industry.
Suggestions. With the progress of society and the rapid development of science and technology, people’s living requirements are increasing day by day, and the requirements for automobiles are naturally getting higher and higher. Especially in the driverless area, the driverless car launched by Google Company also happened in 2016, which shows that Google’s driverless car still has defects, but the intelligent control of automobiles is the future. A trend. This paper is based on the research of dual-vehicle communication control system of electromagnetic navigation intelligent vehicle based on NZP Kinetis MK60FN1M0VLQ15 microprocessor.
The system involves road identification, hardware production, power management, algorithm control and so on. Intelligent vehicle control system is a comprehensive control system which integrates multi-functions such as path recognition, path planning, role recognition, multi-level driving assistance and so on. Core board module: using NZP Kinetis series MK60FN1M0VLQ15 microcontroller, hereinafter referred to as K60. Our team did not insert the chip directly into the motherboard, but used the smallest system board provided by Yamato technology. This advantage is that if the chip burns, the system board can be replaced in time without replacing the whole motherboard. Finally, according to the size of B model, the size of the motherboard is determined to be a circular rectangle of 12 cm*5 cm. Power module: K60 chip, electromagnetic sensor, and motor module need 5V power supply. TPS76850 chip is used to provide stable voltage. It can work at very low voltage drop and is proportional to the output current, so it is very stable. In order to ensure the stability of power supply for motor and motherboard, two TPS76850 power supply solutions are adopted. LM2941 chip is used to supply power to the steering gear. The power supply circuit composed of LM2941 can provide adjustable voltage output to ensure flexible steering of the steering gear on the track. Steering module: The model steering gear is SD5 steering gear, which is a special type. Its working voltage can only be less than 5.5V. It has the function of stop-up protection. The steering gear starts to protect after 3 seconds of stop-up. It reduces the current, protects the motor and the mainboard’s normal working current 200 mA, the stop-up current 800 mA, and the frequency is 300 HZ. The “H bridge drive circuit” is composed to drive. The 12V voltage required for the driver chip of HIV 4082 is obtained by boosting the chip of mc34063, which theoretically rises to 12V, but the actual test is about 13.8V. Electromagnetic sensor module: The copper wire with alternating current of 20 kHz and 50 mA is laid in the middle of the electromagnetic track as the lead wire of the vehicle model. According to Maxwell’s theory of electromagnetic field, the variable magnetic field can be produced around the variable current. According to Biot-Savart theorem, the current element can excite the induced electromotive force in the magnetic field. Therefore, the combination of inductance and capacitance is used as the sensor to collect signals on the fine copper line. The function of inductance is similar to that of current element, and the function of capacitance keeps the signal stable. The signal is processed by AD0832 chip, and the collected signal is amplified and sent to MK60 for processing. Human-computer interaction module: using dial switch, key and OLED. Because the friction coefficient of each track is different, the development of dial codes and four keys can form different gears to adapt to different environments. OLED can display some basic output of debugging vehicle model, such as the output of acquisition signal, key gear and PID parameters, and the combination of keys can achieve fine-tuning, so that the parameters of the car can be more accurate. Communication module: NRF24L01 is used as communication mode and Yuanyang ultrasonic is used as two kinds of sensors to detect the distance between two modes to complete the overtaking between two vehicles. There are many sections in the track, such as circles, intersections and so on, to simulate the real environment of the road. When the current vehicle model detects the cross or circle, NRF24L01 sends out a request for overtaking signal. After the car behind receives the signal, it chooses to overtake and completes the response sign signal. When the two cars are on the straight road, the Yuanyang ultrasonic ranging module can detect the distance between the two models and adjust the optimal distance between the two vehicles. Electromagnetic sensors (usually referred to as forward-looking) are 25 centimeters vertical from the ground and 30 centimeters horizontal from the head. The prospects are made up of six sensors in a row. The next two are 10 mH inductors with 45 degrees inclination, the last two are horizontal inductors, and the other two are vertical inductors between inclination and level, labeled 0.412.53. Vertical inductance detection cross, if the inductance of each other four routes is directly above the guide line, thermostatic element the inductance of this route is the largest, so according to this to find the sensor with the largest inductance value, so as to judge the position of the car on the track. There are five positions of the car, the left side of 0, the right side of 01, the 12, the 23 and the 3. The difference of these five positions is reflected in the difference of inductance between the two middle paths. The steering gear can be steered according to the difference. After testing, the control method of positional PD can get better results. The idea of PID is to use the difference between the real feedback value and the expected value to accurately stabilize a certain quantity. This is widely used in motors. In motor PID regulation, according to the deviation between the real speed measured by the encoder and the speed you want the car to reach, the system can be quickly stabilized. Then through the speed curve transmitted by Bluetooth, the slope of the curve can be used to judge whether the system can achieve stability quickly. It is a very tedious task to describe the steering of a car and its real-time coordination with the motor with an accurate mathematical model. Generally speaking, the car on the track only needs three points to cooperate well – electromagnetic sensor detection, steering, motor power. Hardware connection should not be problematic. That is, the positional PD of the steering gear and the incremental PI of the motor need to be properly coordinated. Why need the fuzzy PID control? Because the car needs different PID to achieve the best state in different positions on the track. At this time, different PIDs can be selected according to different positions, such as straight road, big S bend, small S bend, circle, and debug the PID suitable for these positions. At this time, it is called piecewise PID, but for example, in big S bend and circle. The sudden change of PID at the joints of small S-bends and straight and curves will cause some unexpected problems. At this time, the fuzzy PID control is introduced. The fuzzy controller consists of fuzzy interface, rule base, fuzzy reasoning and clear interface. The fuzzification interface is to fuzzify the obtained deviation into a domain. Rule base includes parameter base of fuzzy controller and rule base of fuzzy control. Fuzzy control rules are based on linguistic variables. Language variables are defined as such fuzzy subsets as “big”, “medium” and “small”. The membership functions of each fuzzy subset indicate the degree to which the exact values on the basic universe belong to the fuzzy subset. Therefore, in order to establish the rules of fuzzy control, it is necessary to merge the exact values in the basic universe into the fuzzy subsets according to the membership function, so that the exact values can be replaced by the linguistic variable values (large, medium, small, etc.). Fuzzy reasoning is to transform the precise input into the fuzzy quantity in two ways: to transform the precise quantity into the fuzzy single point set on the standard universe, and to transform the precise quantity X into the basic element on the standard universe X through the corresponding relation G. Or the exact quantity can be transformed into a fuzzy subset on the standard domain, and the exact quantity can be transformed into a basic element on the standard domain through corresponding relations. The fuzzy subset with the largest membership degree on the element is the fuzzy subset corresponding to the accuracy. The fuzzy subset derived from the clearer interface reasoning should be converted to the exact value to obtain the final control output Y. At present, two methods of accuracy are commonly used.
Result. Center of gravity method: The membership function of the inferred fuzzy subset and the standard universe elements corresponding to the center of gravity of the area surrounding abscissa coordinates are taken as the exact results. After getting the exact value of the reasoning result, the final control output Y should be obtained according to the corresponding relationship. The idea of “point brake”: First of all, the speed control of the car must be closed-loop control. If the five locations of road detection above are between 12, it means that the car is always in the middle of the track. At this time, the speed that the car wants to achieve is the maximum speed you set, and the car is constantly accelerating, because the PID is always trying to achieve the desired speed in the algorithm and maintain stability. But after the straight road suddenly encounters a sharp bend, then the position of the road detection must not be straight, is the left side of 0 or the right side of 3. At this time, a counter is opened, and the speed of self-feedback is continuously added. When the speed of self-feedback is added to a value set in the algorithm, then the value of the counter is zero, so that a section can be clearly seen. The braking distance, which is related to the set value and the length of the sharp bend, needs to be adjusted slowly. Overtaking refers to overtaking when the car behind exceeds the car in front of the ring or cross, and does not collide. After overtaking, it can still drive safely on the track, which is called overtaking. There are two kinds of rings, one is the left part of the ring and the right part of the ring is 1:1, the other is the right part of the left part of the ring is 3:1. When the car enters the 1:1 ring, the guiding line is similar to the “T-shaped”. The car in front will inevitably enter the left ring or the right ring after detection. If it enters the right ring, it will stop and send a signal to the car behind through NRF24L01 to tell it that it enters the right ring, and the car behind will walk the left ring. In the detection algorithm mentioned above, when the “T” shape is detected, the maximum value in the four channels is the inductance on both sides. When the rear car receives the signal, if it detects the maximum inductance on the left, it will naturally go to the left. But if it detects the maximum inductance on the right, the code will force the exchange of inductance on the left and right sides. The inductance on the left side after the exchange is the largest, so the car will still walk on the left side of the ring. Similarly, if the front car enters the left ring first, the rear car enters the right ring. The 3:1 ring has been tested.
Because of the long body of the electromagnetic vehicle, it can hardly overtake at the 3:1 ring, so there is no design. In addition to overtaking at intersections, the 452 routes in road detection are used to detect crosses. When crosses are detected, they will turn into corners to let off the track and send signals to the car behind them. When the car behind receives signals to complete overtaking and send signals to the car behind them, the car that turns into the corners before then receives signals and returns to the track and sends them back to the track. Signaling. After testing, two cars can overtake steadily at the intersection. The mandarin duck module can measure the distance between two vehicles on the straight road. Both the front and rear of the two vehicles are equipped with a mandarin duck module to achieve the solution of controllable distance. Based on Enzhipu Intelligent Vehicle Competition, this paper designs an integrated system involving hardware planning, circuit making, automatic speed measurement, algorithm control analysis, electromechanical, communication and other disciplines. It also exercises the students’practical ability, thinking ability and team cooperation ability. Author’s brief introduction: Chen Lei (1995-), male, Tongling, Anhui Province, undergraduate, research direction: embedded system design.