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Huang W.-Y.,Shandong University | Cheng Y.,Shandong University | Ji S.-B.,Shandong University | Zhang H.-B.,Shandong Baoya New Energy Vehicle Co.
Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology | Year: 2013

EV energy consumption was affected by driver's driving characteristic and could be lowered by perfect driving manners. The difference of energy consumption driving by different drivers was tested and driving characters of affecting the difference were discussed according to test results of electric vans running in Ji'nan city. Factors influencing EV energy consumption, such as vehicle acceleration, speed, energy recovery, driving cycle and motor overload were tested and analyzed. By vehicle controller, motor torque and over-speed were controlled, and therefore driving parameters to which energy consumption was sensitive were optimized. The test of optimized electric vans is carried out, and results indicated that energy consumption of optimized vans is lowered and insensitive to different drivers. Compared to the original one, energy consumption of optimized vans could be decreased as more as 34.94%. Source


Huang W.-Y.,Shandong University | Cheng Y.,Shandong University | Ji S.-B.,Shandong University | Li C.,Jinan Electrical Vehicle Operation Co. | And 2 more authors.
Dianji yu Kongzhi Xuebao/Electric Machines and Control | Year: 2012

A control strategy of Electric Vehicle (EV) powertrain under dynamic operation conditions was optimized in order to lower power consumption and prolong EV's endurance mileage. Based on measured data from an AC asynchronous motor and a LiFePO4/C Li-ion battery pack, a powertrain's working efficiency describing model was developed. An optimal control method to improve EV powertrain's efficiency was deduced following the model. To verify the method, a powertrain's simulating model was established, and its validation was conformed in contrast to the results of experiments. An EV's start acceleration process control strategy was optimized according to the simulating results, and the strategy was implemented in the test bench. The testing results show a 3.3% efficiency improvement of the new strategy over the original one, which suggests that this powertrain efficiency model can be used to optimize the control strategy at dynamic operation conditions. Source


Huang W.-Y.,Shandong University | Cheng Y.,Shandong University | Cao H.,Shandong University | Zhang H.-B.,Shandong Baoya New Energy Vehicle Co.
Dianji yu Kongzhi Xuebao/Electric Machines and Control | Year: 2012

An energy feedback control strategy of EV was proposed for coasting and braking processes reference for the characteristics of Jinan's vehicle driving-cycle. The driving-cycle was constructed based on real vehicle data, and recoverable energy speed characteristic as well as control strategy's evaluation basis was discussed. A control strategy was developed for coasting condition depending on energy feedback efficiency model and contrasting to conventional vehicles coasting resistance. Torque impact, which occurred at torque changing sharply, was avoided by adopting dynamic matrix control (DMC). A brake energy feedback control strategy was designed referring to wheel slip rate. Real vehicle testing results verify that there are about 30% mean energy feedback efficiency and 10% energy consumption improvement of the new strategy over the original one, and about 84% recoverable energy has been recycled by the new strategy according to Jinan's vehicle driving-cycle. Source


Huang W.,Shandong University | Cheng Y.,Shandong University | Ji S.,Shandong University | Li C.,Jinan Electrical Vehicle Operation Co. | And 2 more authors.
Qiche Gongcheng/Automotive Engineering | Year: 2013

For improving the efficiency of the power drive system of battery electric vehicle, the Simulink and Stateflow modules of Matlab software are used to develop a driving control strategy for battery electric vehicle, consisting of acceleration pedal signal processing module, driving mode identification and switching strategy and control strategies for each driving mode. With the strategy, incremental PID control based on vehicle speed deviation is adopted in steady mode, the control is exerted following the optimum path for efficiency in transient mode and the output power of motor is limited in failure mode. To verify the strategy, a simulation model for power drive system is built and simulation and real vehicle test are conducted. The results show that the control strategy developed is effective and can enhance the efficiency of power drive system and hence extend the driving range of battery electric vehicle. Source

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