Search Results

A DMS500 engine exhaust particle size spectrometer was employed to characterize the effects of injection strategies on particulate emissions from a turbocharged gasoline direct injection (GDI) engine. The effects of operating parameters (injection pressure, secondary injection ratio and secondary injection end time) on particle diameter distribution and particle number density of emission were investigated. The experimental result indicates that the split injection can suppress the knocking tendency at higher engine loads. The combustion is improved, and the fuel consumption is significantly reduced, avoiding the increase in fuel pump energy consumption caused by the 50 MPa fuel injection system, but the delayed injection increases particulate matter emissions.

The fuel-saving potential of a series hybrid electric vehicle (SHEV) was investigated in this work based on the future goals and technical roadmaps proposed by China's automobile and internal combustion engine (ICE) industry. The genetic algorithm optimization method and dynamic programming energy management strategy are used to optimize the key component parameters of a typical SHEV SUV to improve the fuel economy of the vehicle. Results showed that the fuel consumption of the vehicle would be 3.24 L / 100km in 2035, which is 37.21% less than 5.16 L / 100km in 2020, following the industries’ roadmaps. The results also indicated that the improvement of the ICE’s thermal efficiency is the main reason for the decrease of the vehicle’s fuel consumption. In addition, the improvement of working points and the reduction of energy losses of the key components also contribute to the improvement of the fuel economy.

SEAT Department of SAIC Motor Vehicle Company starts innovatively applying the single motor and P2.5 configuration scheme from EDU G2(Electric Drive Unit Generation 2), which consists of six engine gears and four motor gears. EDU G2 is very compact and adaptable through the coupling design. Gear coupling make the engine and motor coordination limited, so as to the high efficiency zone of the engine and the high efficiency zone of the motor cannot match in some working conditions, which affect the performance of the vehicle. Therefore, SEAT developed the second generation of single-motor plug-in hybrid system EDU G2 Plus EDU G2(Electric Drive Unit Generation 2 Plus), which realized the decoupling design of 5 engine gears and 2 motor gears, so that the power output of engine and motor is freely. With excellent power and economic performance, the vehicle has been well received by customers.

The roof sensor system is an indispensable part of intelligent vehicles to observe the environment, however, it deteriorates the aerodynamic and noise performance of the vehicle. In this paper, large eddy simulation and the acoustic perturbation equation are combined to simulate the flow and sound fields of the intelligent vehicle. Firstly, test and simulation differences of aerodynamic drag and pressure coefficients on the roof and rear of the intelligent vehicle without roof sensor system are discussed. It is found that the difference in aerodynamic drag coefficient is 5.5%, and the pressure coefficients’ differences at 21 out of 24 measurement points are less than 0.05. On this basis, under the influence of the sensor system, the aerodynamic drag coefficient of the intelligent vehicle is increased by 23.4%.

The temperature management of the proton exchange membrane fuel cell cooling system is very important to the stability and life of the engine. The size and cycle switching of the cooling system and the rapid temperature rise of the system are inseparable from the thermostat. In this paper, a simulation model of the fuel cell cooling system is built for a 30KW fuel cell system, and its accuracy is verified by experiments. The temperature fluctuation of the system in the confluence mode is mainly studied, and the error is about 0.9 °C. The influence of the converging mode of the thermostat on the temperature of the cooling system is researched through the simulation platform. Based on the simulation model, the influence of thermostats with different external environments and opening degrees on the size cycle switching of cooling system is predicted, which provides optimization and guidance for the system control strategy.

Electric vehicle sharing (EVS) can alleviate traffic congestion and reduce emissions. However, the poor user experience and lack of word-of-mouth effect lead to the low utilization rate of EVS in China. Based on the demand and pain points of EVS, this paper concentrates on travel mode choice behavior of consumers under social networks and establishes an agent-based model for EVS diffusion. The results show that: (1) Social networks can promote the diffusion of EVS and the number of opinion leaders and the number of fans of opinion leaders play an important role. (2) Consumers are more sensitive to travel costs than non-travel time now, but with the improvement of demand for travel experience, consumers are more concerned with non-travel time. (3) The non-travel time of EVS needs to be reduced to 9, 8 and 7 minutes respectively to retain users when the travel cost increases to 0.7, 0.8 and 0.9 Yuan/minute.

High altitudes have a significant effect on the real driving emissions (RDE) of vehicles due to lower pressure and insufficient oxygen concentration. In addition, type approval tests for light-duty vehicles are usually conducted at altitudes below 1000 m. In order to investigate the influence of high altitude on vehicles fuel economy and emissions, RDE tests procedure had been introduced in the China VI emission regulations. In this study, the effect of altitude on fuel economy and real road emissions of three light-duty gasoline vehicles was investigated. The results indicated that for vehicles fuel economy, fuel consumption (L/100 km) for the tested vehicles decreased while the mean exhaust temperature increased with an increase in altitudes. Compared to near sea level, the fuel consumption (L/100 km) of the tested vehicle was reduced by up to 23.28%.

As a prerequisite for energy management of hybrid vehicles, the results of speed prediction can optimize the performance of vehicles and improve fuel efficiency. Energy management strategies are usually developed based on standard driving cycles, which are too generalized to show the variability of driving conditions in different time and locations. Therefore, this paper constructs a representative driving cycle based on driving data of the corresponding time and location, used as historical information for prediction. We propose a method to construct the driving cycle based on Markov chain theory before constructing the prediction model. In this paper, multiple prediction methods are compared with traditional parametric methods. The difference in prediction accuracy between multiple prediction methods under the single time scale and multiple time scale were compared, which further verified the advantages of the speed prediction method based on Markov chain theory.

The driving conditions of commercial logistics vehicles have the characteristics of combined urban and suburban roads with relatively fixed mileage and cargo load alteration, which affect the vehicular fuel economy. To this end, an adaptive equivalent consumption minimization strategy (A-ECMS) with vehicle speed and weight recognition is proposed to improve the fuel economy for a range-extender electric van for logistics in this work. The driving conditions are divided into nine representative groups with different vehicle speed and weight statuses, and the driving patterns are recognized with the use of the bagged trees algorithm through vehicle simulations. In order to generate the reference SOC near the optimal values, the optimal SOC trajectories under the typical driving cycles with different loads are solved by the shooting method and the optimal slopes for these nine patterns are obtained.

Improving the heat dissipation performance of the engine radiator in the real working environment is of great significance to the cooling of the engines. The purpose of this paper is to study the influence of the radiator’s geometric parameters on its heat dissipation performance in the cooling module environment and optimize the geometric parameters to improve the heat dissipation performance of the radiator. Based on the performance data obtained from relevant component tests and the engine thermal balance test, the simulation model of the engine thermal management system is established, and the reliability of the model is verified. The heat dissipation performances of the single radiator and the radiator in the cooling module are compared by using the validated model.

The layout of component in the engine compartment affects the fluid flow performance, thereby affects the thermal management performance. Based on the fluid flow performance in the engine compartment of an SUV, this paper proposes local optimization plans of the cooling module—moving downward the oil cooler and forward the intercooler, tilting an angle of the cooling module and shifting the fan. This paper took the fan center temperature as the optimization goal and set three levels for the four factors. It was found that the deviation of the fan has the most significant impact on fan center temperature among four factors. Then we discovered that the interaction between the factors has a significant impact on the air intake volume of the cooling module.

This study investigated the plastic deformation behavior of 304 stainless steel thin-walled tubes under axial compression by means of numerical calculation and theoretical analysis. It was found that the plastic deformation length of thin-walled tube determined the formability of folds and the work done in the whole axial compression process. To reveal the relation between the range of plastic deformation length and tube geometry parameters, regression equations were established using the quadratic regression orthogonal design method. Experiments were conducted to validate the equations. The process windows for forming a single fold and tube joining at ends had been printed ultimately. The results showed that the regression equations can accurately predict the range of plastic deformation length for forming a single fold.

Diesel engine is vital in the industry for its characteristics of low fuel consumption, high-torque, reliability, and durability. Existing diesel engine technology has reached the upper limit. It is difficult to break through the fuel consumption and emission of diesel engines. VVA (Variable Valve Actuation) is a new technology in the field of the diesel engines. In this paper, GT-Suite and ANN (artificial neural network) model are established based on engine experimental data and DoE simulation results. By inputting Intake Valve Opening crake angle (IVO), Intake Valve Angle Multiplier (IVAM) and Exhaust Valve Angle Multiplier (EVAM) into the ANN Model, and by using SA (simulated annealing algorithm), the optimized results of intake and exhaust valve lift under the target conditions are obtained.

In this work, the influences of various real-timely available energy management strategies on vehicle fuel consumption (VFC) and energy flow of a range-extender electric vehicle were studied The strategies include single-point, multi-point, speed-following, and equivalent consumption minimization strategy. In addition, the dynamic programming method which cannot be used in real time, but can provide the optimal solution for a known drive situation was used for comparison. VFCs and energy flow characteristics with different strategies under Worldwide Harmonized Light Vehicles Test Cycle (WLTC) were obtained through computer modeling, and the results were verified experimentally on a range-extender test bench. The experimental results are consistent with the modeled ones in general with a maximum deviation of 4.11%, which verifies the accuracy of the simulation models.

CuO-water nanofluids was utilized as heat transfer medium in the cooling system of the diesel engine. By using CFD-Fluent software, for 0.5%, 1%, 3% and 5% mass concentration of nanofluids, 3-dimensional numerical simulation about flow and heat transfer process in the cooling system of engine was actualized. According to stochastic particle tracking in turbulent flow, for solid-liquid two phase flow discrete phase, the moving track of nanoparticles was traced. By this way, for CuO nanoparticles of different mass concentration nanofliuds in the cooling jacket of diesel engine, the results of the concentration distribution, velocity distribution, internal energy variation, resident time, total heat transfer and variation of total pressure reduction between inlet and outlet were ascertained.

A new range-extension hybrid powertrain concept, namely the Tongji Extended-range Hybrid Technology (TJEHT) was developed and demonstrated in this study. This hybrid system is composed of a direct-injection gasoline engine, a traction motor, an Integrated Starter-Generator (ISG) motor, and a transmission. In addition, an electronically controlled clutch between the ISG motor and engine, and an electronically controlled synchronizer between the ISG motor and transmission are also employed in the transmission case. Hence, this system can provide six basic operating modes including the single-motor driving, dual-motor driving, serial driving, parallel driving, engine-only driving and regeneration mode depending on the engagement status of the clutch and synchronizer. Importantly, the unique dual-motor operation mode can improve vehicle acceleration performance and the overall operating efficiency.

With the increasing worldwide concern on environmental pollution, battery electrical vehicles (BEV) have attracted a lot attention. However, it still couldn’t satisfy the market requirements because of the low battery power density, high cost and long charging time. The range-extended electrical vehicle (REEV) got more attention because it could avoid the mileage anxiety of the BEVs with lower cost and potentially higher efficiency. When internal combustion engine (ICE) works as the power source of range extender (RE) for REEV, its NVH, emissions in starting process need to be optimized. In this paper, a 2-cylinder PFI gasoline engine and a permanent magnet synchronous motor (PMSM) are coaxially connected. Meanwhile, batteries and load systems were equipped. The RE co-control system was developed based on Compact RIO (Compact Reconfigurable IO), Labview and motor control unit (MCU).

The CO2 reduction request for automotive industry promotes the efforts on the engine thermal efficiency improvement. The goal of this research is to improve the thermal efficiency on an extremely downsized 3-cylinder 1.0 L turbocharged gasoline direct injection engine. Effects of compression ratio, exhaust gas recirculation (EGR), valve timing and viscosity of oil on fuel economy were studied. The results show that increasing compression ratio, from 9.6 to 12, can improve fuel economy at relative low load (below 12 bar BMEP), but has a negative effect at high load due to increased knock intensity. EGR can significantly reduce the pumping loss at low load, optimize combustion phase and reduce exhaust gas temperature. Therefore, the fuel consumption is reduced at all test points. The average brake thermal efficiency (BTE) benefit percentage is 3.47% with 9.6 compression ratio and 5.33 % with 12 compression ratio.

Emissions of diesel engine have been received much more attention since the Volkswagen Emission Scandal. The Euro VI emission standard has already included cold start emissions in the legislative emission driving cycles which is one of the hardest part of emission control. High altitude performance is also considered in the latest regulations which will be stricter in the future. Heating the coolant is one of the most common method to improve the cold start performance. But researches focus on the emission of a diesel engine in different coolant temperature at high altitude which up to 4500m have not been seen. The present research investigated the effect of coolant temperature on performance and exhaust emissions (gaseous and particulate emissions) during the cold start of a diesel engine. A plateau simulation system controlled the inlet and exhaust pressure to create altitude environments from 0m to 4500m, and the coolant temperature was controlled from 20°C to 60°C.

Carbon fiber reinforced plastic (CFRP) composite materials have gained particular interests due to their high specific modulus, high strength, lightweight and perfect corrosion resistance. However, in reality, CFRP composite materials cannot be used alone in some critical places such as positions of joints with hinges, locks. Therefore, metal reinforcements are usually necessary in local positions to prevent structure damage. Besides, if uncertainties present, obtained optimal structures may experience in failures as the optimization usually pushes solutions to the boundaries of constraints and has no room for tolerance and uncertainties, so robust optimization should be considered to accommodate the uncertainties in practice. This paper proposes a mixed topology method to optimize metal and carbon fiber reinforced plastic composite materials simultaneously under nondeterministic load with random magnitude and direction.