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OBD (On-Board Diagnostic) test system is applied to research influences of environmental parameters (altitude and environment temperature) on real-world NOx emission and fuel consumption for heavy-duty diesel trucks in this paper. The research results indicate that altitude and environment temperature have great influence on NOx emission rate and fuel consumption. High altitude in range of 3000~4000 m results in NOx emission rate is lower than low and moderate temperature because of air intake amount decreasing. However the fuel consumption rate is higher than lower altitude because altitude influences real-time changes of air inflow and combustion conditions in the cylinder of the engine. NOx emission rate and fuel consumption is more stable at different vehicle speed, VSP and RPM at high altitude, and NOx emission rate fluctuate dramatically at low and moderate altitude. The fuel consumption rate is higher at 10~20 °C than that at lower and higher temperature.

Homogeneous Charge Induced Ignition (HCII) combustion utilizes a port injection of high-volatile fuel to form a homogeneous charge and a direct injection of high ignitable fuel near the Top Dead Center (TDC) to trigger combustion. Compared to Conventional Diesel Combustion (CDC) with high injection pressures, HCII has the potential to achieve diesel-like thermal efficiency with significant reductions in NOx and PM emissions with relatively low-pressure injections, which would benefit the engine cost saving remarkably. In the first part of current investigation, experiments were conducted at medium load with single diesel injection strategy. HCII exhibited great potential of using low injection pressures to achieve low soot emissions. But the engine load for HCII was limited by high heat release rate. Thus, in the second and third part, experiments were performed at high and low load with double diesel injection strategy.

Due to the rapid development of road infrastructure and vehicle population in China, the fuel consumption and emission of on-road vehicles tested in China World Transient Vehicle Cycle (C-WTVC) cannot indicate the real driving results. But the test results in China Heavy-duty Commercial Vehicle Test Cycle-Coach (CHTC-C) based on the road driving conditions in China are closer to the actual driving data. In this paper, the model for predicting the performance of heavy-duty vehicles is established and validated. The fuel consumption and NOx emission of a Euro VI heavy-duty coach under C-WTVC and CHTC-C tests are calculated by employing the developed model. Furthermore, the fuel consumption of the test coach is optimized and its sensitivity to the driving factors is analyzed.

Compressed Natural Gas (CNG), because of its low cost, high H/C ratio, and high octane number, has great potential in automotive industry, especially for heavy-duty commercial vehicles. However, relative slow flame speed of natural gas leads to long combustion duration and low thermal efficiency and tends to cause knock combustion at high load, which will aggravate engine thermal load and reliability. Enhancing turbulence intensity in combustion chamber is an effective way to accelerate flame propagation speed and improve combustion performance. In this study, the flow simulations of several piston bowls with different inner-convex forms were carried out using three-dimensional computational fluid dynamics (3D-CFD) software CONVERGE. The numerical results showed the piston bowls with inner-convex could disturb the charge swirl motion and enhance turbulence of different intensity. A hexagram geometry bowl was proved to have the best function in strengthening turbulence intensity.

In this study, with the aim of reducing fuel consumption and improving power performance, the optimization for the driveline parameters of a self-dumping truck was performed by using a vehicle performance simulation model. The accuracy of this model was checked by the power performance and fuel economy tests. Then the transmission ratios and final drive ratio were taken as design variables. Meanwhile, the power performance of the self-dumping truck was evaluated through standing start acceleration time from 0 to 70km/h, maximum speed and maximum gradeability, while the combined fuel consumption of C-WTVC drive cycle was taken as an evaluation index of fuel economy. The multi-objective optimization for the power performance and fuel economy was then performed based on particle swarm optimization algorithm, and the Pareto optimal set was obtained. Furthermore, the entropy method was proposed to determine the weight of fuel consumption and acceleration time.

Hydraulic retarder, as an auxiliary braking device, is widely used in commercial vehicles. Nowadays, the hydraulic retarder’s internal oil is mainly cooled by the coolant circuit directly. It not only aggravates the load of engine cooling system, but also makes the abundant heat energy not be recycled properly. In this study, an independent energy supply device with organic Rankine cycles is applied to solve the problems above. In the structure of this energy supply device, the evaporator’s inlet and outlet is connected in parallel with the oil outlet and inlet of the retarder respectively. A part of oil enters the evaporator to transfer heat with the organic fluid, and the rest of oil enters the oil-water heat exchanger to be cooled by the coolant circuit. According to the different braking conditions of the retarder, the oil temperature in the inlet of the hydraulic retarder can be kept within the proper range through adjusting the oil flow rate into the evaporator properly.

A full drive-by-wire electric vehicle, named Urban Future Electric Vehicle (UFEV) is developed, where the four wheels' traction and braking torques, four wheels' steering angles, and four active suspensions (in the future) are controlled independently. It is an ideal platform to realize the optimal vehicle dynamics, the marginal-stability and the energy-efficient control, it is also a platform for studying the advanced chassis control methods and their applications. A centralized control system of hierarchical structure for UFEV is proposed, which consist of Sensor Layer, Identification and Estimation Layer, Objective Control Layer, Forces and Motion Distribution Layer, Executive Layer. In the Identification and Estimation Layer, identification model is established by utilizing neural network algorithms to identify the driver characteristics. Vehicle state estimation and road identification of UFEV based on EKF and Fuzzy Logic Control methods is also conducted in this layer.