Study On The Driving Assistant Of Acceleration Pedal For The Pure Electric Bus

The research of decreasing energy consumption and extension of driving range isa key problem to the development of the pure electric buses besides confronting theenergy crisis and the environmental problems. However, due to inappropriate driverbehaviors the practical endurance mileage of the electric buses are significantlyreduced. In this research, the relationship between the difference of driver behaviorand energy consumption was investigated specifically and it was focused to improvethe practical endurance mileage based on the real-time optimization of driving abilityof the acceleration pedal.The energy optimization algorithm of multi-level programming for the electricbuses, comprised of the driving mission energy programming，the bus station speedprogramming and the preview distance acceleration pedal programming respectively,were put forward, and the pedal programming algorithm was focused to improve theenergy consumption.A data acquisition system based on GPRS network was developed to meet theneed of wireless real-time data recording and remote control variables configuration.An vehicle control unit was developed to drive the electic bus which cancommunicate with the data acquisition system in high communication quality underthe assurance of the wireless communication quality strategy.The relationship between the difference of the driver behavior and energyconsumption was studied through analyzing the main driving fragment of the drivingcycles of the route600electric bus in Tianjin. It shows that47%of the energy wasconsumed in the process of out station and the difference reached28.9%between thedrivers. The essential reason of the difference was the deviaton of the motoroperating path in the efficiency plane which was the result of acceleration pedal usedin different way. The distribution of acceleration pedal was useful to experss theaccuracy of vehicle speed prediction and the tendency of deceleration of drivers in theinlet parking process. The more energy was recycled in the inlet parking process, thehigher efficiency of the energy recovery in the whole driving cycle. An effectivemanagement to the motor operating path in the out station process is very helpful to the improvement of the whole energy consumption besides the minimization of theacceleration dispersion.Several key variables describing the characteristics of driver behavior weredefined, and an effective Gaussian Mixture Model (GMM) identification model of thedrivers, with accuracy higher than93%, was established by extracting the cepstrum ofthe pedal signal besides the key variables mentioned before. A hardware-in-the-loopsimulation model was set up based on dSPACE platform which the key part is thevirtual driver model with real characteristics of the driver based on the Radial BasisFunction (RBF) network.A vector set of driving characteristics of an electric bus driver was defined and amultidimensional linear space was used to describe the running track of the drivingstatus. The torque demand was predicted against historical running tracks withaccuracy of over88%in the driving characteristics vector set of the driver which wasidentified before. The pedal programming algorithm was constructed based on thefuture torque demand prediction. A model predictive control strategy was developedto obtain active management of the driver behavior, in order to minimize the deviationbetween the current and target car speed.Simulation results showed that the acceleration dispersion of the electric bus wasreduced and10.5%of the energy was saved. Experimental results showed that thedriver was not significantly influenced by the regulating process, and7.2%of theenergy was saved.