Control Strategy Of HEV Based On The Driving Cycle And Driver Intention Recognition

With the flourishing development of automobile industry and the continuous augment of production and ownership of automobile, automobile has also become a major contributor to environmental pollution and energy crisis. In order to alleviate the pressure of the environment and energy, it is urgent to saveenergy and reduceemission for vehicle. The research and development of hybrid energy vehicles (HEV) is an effective way and a must forenergy saving and emission reduction, transformation of the automobile industry and technology upgrades. As the soul of HEV, Vehiclecontrol strategy is the key technology to hybrid vehicles. This subject first classifies and constructs citystandard driving cycle. Then based on the research of driving cycle identification method and the driving intention identification method, associated control strategy is provided and verified by the results of simulations.First of all, current city standard driving cycle is a unify standard, but actually traffic condition is changeable, so if thecitystandard driving cycle is constructeddetailed, the character ofcity standard driving cycle will be better reflected. Considering the road type and congestion of traffic, city cycle is proposed to be divided into four types in this subject and the four construction method of standard city cycle based on secondary clustering is provided. On the basis of amount of data accumulated for many years from hybrid city bus remote monitoring and data acquisition system, Dalian’s fourtype driving cycle is constructed.Second, this paper studies the identification method of driving cycle. Fuzzy pattern recognition method which integrates pattern recognition and artificial intelligenceis applied and it is the first time to utilize new architecture fuzzy pattern recognition which has been successfully applied in civil engineering to identify driving condition avoiding the disadvantage traditional recognition method, basing on fuzzy pattern recognition method this subject constructs a fuzzy recognition cycle simulation model and do the experiment.realizes the accurate identification.Next, only by displacement of the accelerator pedal and brake pedal to identify the driver’s intent will lead to the problems of identification inaccuracy. So this paper presents a multi-parameter driver intention recognition method on the basis of fuzzy reasoning, which divides the diver intention recognition into7categories. By seeing the accelerator pedal displacement and its change rate, the brake pedal displacement and its change rate and vehicle speed as input parameters, an accurate identification isrealized based on fuzzy reasoning.Finally, in views of the problem that the driving cycle and driver intention cannot be considered at the same time which will lead to the control can’t be roundly.based on the deeply research oncycle recognition method anddriver intention recognition, we raised a "multi-driving cycle dynamic logical threshold" control strategy based on cycle recognition, balance coalition of logical threshold and SOC" accelerate strategy of driver intention recognition,"stepped brake energy recovery "braking strategy, and the control strategy of driving cycle and ofdriver intention. We demonstrated the greatly oil conservation in both strategy of driving cycle recognition and strategy of driver intention recognitionby simulation model, and the joint control strategy has a better effect combining the two’s advantages compared to the ones without combined.