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The electronic control system of the variable nozzle turbocharger (VNT) was designed. The actuator is the electro-hydraulic servo proportional solenoid. The signals of the engine pedal position sensor, the engine speed sensor, the boost pressure sensor, the intake air temperature sensor, and the ambient pressure sensor are sampled and filtered. The engine working condition is estimated. The control algorithm was designed as the closed-loop feedback digital PI control together with the open-loop feed forward control. The gain-scheduled PI control method is applied to improve the robustness. The control system was calibrated at the turbocharger test bench and the engine test bench. The results indicate the designed control system has good performance for the boost pressure control under the steady and transient conditions.

In low-temperature environment, heat supply requires considerable energy, which significantly increases energy consumption and shortens the mileage of electric vehicle. In the fuel cell vehicles, waste heat generated by the fuel cell system can supply heat for vehicle. In this paper, a thermal management system is designed for a the fuel cell interurban bus. Thermal management strategy aiming at temperature regulation for the fuel cell stack and the passenger compartment and minimal energy consumption is proposed. System model is developed and simulated based on AMESim and Matlab/Simulink co-simulation. Simulation results show that the fuel cell system can provide about 78 % energy of maximum heat requirement in -20 °C ambient temperature environment.

The lithium-ion battery plays an important role in saving energy and lowering emissions. Many parameters like temperature have an influence on the characteristic of the battery and this phenomenon becomes more serious in an electric vehicle. In this paper, the application of a boost DC/DC converter to the battery system of high power for online AC impedance identification is proposed. The function of the converter is to inject a current excitation signal into the battery at work and the normal output current is drawn by a load. Through analyzing the average state space equations and deriving the small signal model of the converter, the gain function is deduced of the fluctuated current signal against the fluctuated duty cycle which controls the converter. The control algorithm is designed and the system model is verified using Matlab/Simulink with respect to the disturbance current signal generation, the gain function and its variation with frequency range.

An imperceptible engine start is critical to the acceptance of hybrid vehicles. This paper focusses on an optimal control problem that tries to reduce vibration during engine start. Efforts are made to obtain the optimal speed trajectory that could cause minimum vibration during engine start. In the first section, the target diesel powertrain is introduced. A four cylinder diesel engine is coaxially paralleled with an ISG motor. The ISG motor serves as the engine starter and engine flywheel. Its dynamic model is established using crank-link dynamics. Secondly, an index is brought out to evaluate the severity of vibration. The cylinder pressure variation is the main cause of engine torque ripple, which in turn results in engine speed fluctuation. The square of the angular acceleration is chosen as the index of vibration. The index shows a positive relation of cylinder pressure in terms of amplitude.

Electric vehicle (EV) is a worldwide researching focus due to its environmental friendliness, but the inaccurate Remaining Driving Range (RDR) estimation hinders the EVs' popularity, and an accurate determination of the battery Residual Usable Energy (RUE) is the key factor to obtain a precise RDR value. A common RUE estimation method is based on State-of-Charge (SOC) estimation, in which the RUE is proportionally related to the current SOC. However, the battery voltage varies significantly under real-world conditions, and the traditional method results in certain estimation errors. An adaptive RUE prediction method (AEP) is introduced in this paper, in which the dynamic voltage is predicted based on the future discharge profile and a battery model, while the RUE is then calculated by the predicted voltage and current sequences.

In order to reduce driver's anxiety about range and energy, a direct and effective approach is to offer the remaining driving range based on the vehicle's states. Consequently, the estimation accuracy of the battery's remaining energy is very important. This paper introduces a experiment-based model for predicting the remaining energy, which considers many factors, such as current, temperature, difference between battery cells, and so on. This approach ensures the accuracy of the remaining driving range. Finally the method is validated through the environment space test. Validation results show that this method can offer exact remaining energy, which reduces the estimation error of the remaining range greatly.

This paper conducts simulation research on engine torque ripple suppression based on the engine torque observer by using a flywheel-ISG (integrated starter generator). Usually, engine torque can be suppressed by using a passive method such as by installing a flywheel or torsional damper. However, failure problems arise in hybrid system because of different mechanical characters of the engine and its co-axial ISG motor. On the prototype test bench, the flywheel of the engine has been removed and replaced by an ISG rotor, namely FISG (flywheel ISG). Besides, the crank and FISG rotor are directly connected, which means no dampers or clutches are installed. If the engine torque ripples can be suppressed by the same level as the flywheel and damper by FISG active torque compensation, the new system can be more compact and economical. Simulation efforts are made to verify its feasibility. Firstly, based on the experimental test bench, which is currently under construction.