Study Of Somatosensory Control And Driving System Of Smart Scooter

The combination of sensors, control technology and electric drives produces a number of novel personal scooters which provide more choices and convenience for people to travel. The driving style is mainly divided into two, one is somatosensory control and the other is manual control. The features of Good handling, novel functions and simple structure make the research of somatosensory control become an important direction of personal transport area.The core technology of somatosensory control driving is the measurement of body attitude. The attitude detection system is composed of MEMS sensors including triaxial accelerometer, triaxial magnetometer and triaxial gyroscope. Calibration parameters are extracted from the establishment of error model to improve the measurement accuracy of the sensors. Combining relevant knowledge of inertial navigation and digital filtering,according to the different characteristics of these three sensors in measuring acceleration, geomagnetic and angular velocity, data fusion methods are cleverly used to further improve the accuracy of attitude detection.In addition, the smart scooters require the driving system more reliable and compact, so BLDC hub motor is a trend. In this paper, a three-phase quad-pole brushless DC motor which is featured with a trapezoidal back EMF is used as the power. In accordance with the parameters of the motor, the complete simulation model is established in Simulink. The aim is to study the operating characteristics of the BLDC motor, involving angular velocity, back EMF, phase current and line voltage. Meanwhile, the hardware of driving system comprised of a three-phase inverter bridge, signal conversion and isolation, power supply as well as voltage and current detection units is designed. On this basis, TMS320F28335 functioning as a controller is programmed to achieve the goal of motor driving and controlling.The results of simulation and experiment show that the sensor system is more accurate after calibration and the use of fusion algorithm enhances the attitude detecting system’s resistance to vibration and mobile acceleration. The driving circuits prove reliable. At the same time, the BLDCM responses stably, quickly and runs quietly in the control of digital PID.