The Research Of Electric Vehicle Drive Control Strategy Based On Multi-Modes

With the development of society, vehicles make people's lives more convenient. But at the same time, they lead to more serious crises of environmental pollution and energy shortage. Accordingly, as the Ministry of Science and Technology recently proposed the direction of developing "Pure Electric Drive Vehicle", manufactures should regard pure electric vehicles as the core of research. And the concept of production should be transformed from "people fit cars" to "cars fit people" in order to meet different demands of driving.Recently, the technology of multi-driving mode is mature both inside and outside our country. In contrast, the control strategy of most electric vehicles is still single-drive mode, which is lack of flexibility and difference. Many functions cannot be completely shown due to inability of activating some characters of the control system. Additionally, diversified conditions of road environment and drivers'habits leads to different requirements of vehicle performance from differentiated drivers or complicated road conditions.According to the above problems, the procedure of research are as follows:Firstly, the study analyzes driving condition and finds out the general rules of pure electric vehicles" actual driving. The initial data from general rules are classified and extracted by statistical techniques from MATLAB such as averaging method, linear fitting method and discrete method. A typical, representative driving condition mode can be established from the analyses of former data by using the short-trip method from kinematic fragments.Next, according to the character performance of road environment, fuzzy inference and intention recognition of driver control action can be concluded by defining the fuzzy function of acceleration related parameters and accelerator pedal related parameters with fuzzy database. Based on the identification results and the original driving control strategy, two different modes (high dynamic mode and low consumption mode) can be devised. The speed, engine efficiency and battery SOC of different modes can be detected by different accelerator pedal opening in simulated experiment. The normal mode and control strategy curve can be optimized by comparing the dynamic property and economy data of different modes.Finally, pure electric vehicle mode can be constructed on CRUISE simulation platform. In this mode, simulation towards maximum speed and climb gradient, and time of acceleration in different driving mode could be accomplished by introducing the relevant parameters of dynamic system matching for vehicle kinematics, the adjustment of original mode from function module, and C compiling driving control strategy curve.