The Research Of Electric Vehicle Driving Situation Identification And HEV Control Strategy

With the rapid development of China's economy, the energy consumption and environment pollution have become increasingly serious. Hybrid electric vehicle (HEV) has great potential in energy-saving and emission-reducing, and gets a rapid development. For there is a great relationship between the control strategy of HEV and the driving situation, the technology of identifying the vehicle driving situation and the control strategy which based on driving situation identification is very important.A hybrid search algorithm built in this paper, which effectively combines the genetic algorithm and the floating search algorithm. This hybrid search algorithm firstly searches the boundary between driving pattern parameters through adaptive genetic algorithm and gets the universal set of vehicle driving patterns; then selects the best subset using the floating search algorithm. In the hybrid search algorithm, the start point of floating selection algorithm is the best, which is chosen from each cycle of genetic algorithm calculation. So most of the invalid searches can be avoided and the searching time decreased, too.There is a driving situation identify model created in this paper, which is based on the fuzzy-neural network. The input parameter of the model is the best driving pattern subset:average speed v, standard deviation of speedσv, standard deviation of accelerationσa, average deceleration r, number of acceleration/deceleration shifts per 100s where the difference between adjacent local max-speed and min-speed is more than 2km/h N100s, number of acceleration/deceleration shifts per 100s where the difference between adjacent local max-speed and min-speed is more than 10 km/h LN100s, percent of time in deceleration interval is less than -0.60m/s2 and more than-0.96 m/s2ηr1-r2, percent of time in acceleration interval is more than 1.03 m/s2ηa2. The vehicle speed is inputted into identify model using rolling time window. A driving situation identify apparatus is created in this paper, and owns many input-output ports. This identify apparatus is suitable to 12-24 volts, and most kinds of vehicle. The software of identify apparatus is designed according to the module structure, which is good at safeguarding and further development.An anti-interference is also designed in the hardware and software of identify apparatus.A fuzzy control strategy of HEV based on the driving situation identify is created, which has two double-inputs-single-output fuzzy controller. In one of the controller, the inputs are SOC of batteries and motor speed, the output is engine torque coefficient when the engine charging the battery; in the other fuzzy controller, the inputs are SOC of batteries and required torque of vehicle, the output is engine torque coefficient when the engine is compensated by motor. Comparing to one three-inputs-double-outputs fuzzy controller, two double-inputs-single-output fuzzy controllers can simplify the Fuzzy Membership Functions of SOC, which is suitable to the further development and maintain the program of HEV controller.A HEV control strategy which based on the identification of driving situation is also created in this paper, which includes a fuzzy controller strategy library. The parameters of fuzzy controller are optimized by adaptive genetic algorithm, which is aim to get the best consumption economy and emission pollution. Two different fuzzy control strategies, which is respectively suitable to urban and freeway driving cycle of our country, are created and the fuzzy control strategy library is formed. When the HEV is driving, the right fuzzy controller is chosen from the library according to the results of driving identify model, and fuel consumption and emission are improved.The Beijing and Wuhan experiments prove the capacity of the driving situation identify model and driving situation identify apparatus. Comparing to the power auxiliary control strategy, the fuzzy control strategy based on the situation identification can decrease the influence of different driving situations, and make the vehicle geting a better fuel economy in different driving situations.