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This paper presents a study of LPG lean burn in a motorcycle SI engine. The lean burn limits are compared by several ways. The relations of lean burn limit with the parameters, such as engine speed, compression ratio and advanced spark ignition etc. are tested. The experimental results show that larger throttle opening, lower engine speed, earlier spark ignition timing, larger electrode gap and higher compression ratio will extend the lean burn limit of LPG. The emission of a LPG engine, especially on NOx emission, can be significantly reduced by means of the lean burn technology.

This paper presents an experimental study of the emission characteristics of a small Spark-Ignited, LPG engine. A single cylinder, four-stroke, water-cooled, 125cc SI engine for motorcycle is modified for using LPG fuel. The power output of LPG is above 95% power output of gasoline. The emission characteristics of LPG are compared with the gasoline. The test result shows that LPG for small SI engine will help to reduce the emission level of motorcycles. The HC and CO emission level can be reduced greatly, but NOx emissions are increased. The emission of motorcycle using LPG shows the potential to meet the more strict regulation.

An air-cooled, four-stroke, 125 cc electronic gasoline fuel injection SI engine for motorcycles is altered to burn ethanol fuel. The effects of nozzle orifice size, fuel injection duration, spark timing and the excess air/ fuel ratio on engine power output, fuel and energy consumptions and engine exhaust emission levels are studied on an engine test bed. The results show that the maximum engine power output is increased by 5.4% and the maximum torque output is increased by 1.9% with the ethanol fuel in comparison with the baseline. At full load and 7000 r/min, HC emission is decreased by 38% and CO emission is decreased 46% on average over the whole engine speed range. However, NOx levels are increased to meet the maximum power output. The experiments of the spark timing show that the levels of HC and NOx emission are decreased markedly by the delay of spark timing.

The platooning of connected automated vehicles (CAV) possesses the significant potential of reducing energy consumption in the Intelligent Transportation System (ITS). Moreover, with the rapid development of eco-driving technology, vehicle platooning can further enhance the fuel efficiency by optimizing the efficiency of the powertrain. Since road grade is a main factor that affects the energy consumption of a vehicle, the estimation of the road grade with high accuracy is the key factor for a connected vehicle platoon to optimize energy consumption using vehicle-to-vehicle (V2V) communication. Commonly, the road grade is quantified by single consumer grade global positioning system (GPS) with the geodetic height data which is rough and in the meter-level, increasing the difficulty of precisely estimating the road grade.

This paper presents the development of an electronic control LPG gas injection system and its application in a small SI engine. The tests results show that the developed LPG gas injection system can meet the needs for the goal of high engine power output and low exhaust emissions based on the engine bench tests. With the LPG electronic gas injection system, the air-fuel ratio can be optimized based on the requirements and CO and NOx emission levels are decreased significantly compared with the LPG mechanical mixer fuel supply system, based on the same HC emission levels. With the new gas phase LPG electronic control injection system, the HC emission level is controlled below the 300 ppm under most engine conditions and under 200 ppm when the engine speed is over 3000 r/min. The NOx emission level is under 2600 ppm in the whole range of engine operation conditions and is decreased by 2000 ppm compared with the LPG mechanical mixer system.

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.

In this study, an experimental investigation was conducted using a direct injection single-cylinder diesel engine equipped with a test common rail fuel injection system to clarify how dimethyl ether (DME) injection characteristics affect the heat release and exhaust emissions. For that purpose the common rail fuel injection system (injection pressure: 15 MPa) and injection nozzle (0.55 × 5-holes, 0.70 × 3-holes, same total holes area) have been used for the test. First, to characterize the effect of DME physical properties on the macroscopic spray behavior: injection quantity, injection rate, penetration, cone angle, volume were measured using high-pressure injection chamber (pressure: 4MPa). In order to clarify effects of the injection process on HC, CO, and NOx emissions, as well as the rate of heat release were investigated by single-cylinder engine test. The effects of the injection rate and swirl ratio on exhaust emissions and heat release were also investigated.

To address the issue of PID control for automotive vibration, this paper supplements and develops the evaluation of automotive vibration characteristics, and proposes a vibration response quantity for evaluating the energy dissipation characteristics of automotive vibration. A two-degree-of-freedom single wheel model for automotive vibration control is established, and the conventional vibration response variables for ride comfort evaluation and the energy consumption vibration response variables for energy dissipation characteristics evaluation are determined. This paper uses the Adaptive Differential Evolution (ADE) algorithm to tune the PID control parameters and introduces an adaptive mutation factor to improve the algorithm's adaptability. Several commonly used adaptive mutation factors are summarized in this paper, and their effects on algorithm improvement are compared.

A novel non-destroy repeatable-use impact theory based total cylinder sampling system has been established. This system is mainly composed of a knocking body and a sampling valve. The knocking body impacts the sampling valve with certain velocity resulting in huge force to open the sampling valve and most of the in-cylinder gas has been dumped to one sampling bag for after-treatment. The feasibility and sampling response characteristics of this impact theory based total cylinder sampling system were investigated by engine bench testing. Within 0 to 35°CA ATDC (Crank Angle After Top Dead Center) sample timing 50 percent to 80 percent of in-cylinder mass would be sampled, which was a little less compared with the traditional system. The half decay period of pressure drop was 10 to 20 degrees crank angle within 0 to 60°CA ATDC sample timing, which was about 2-3 times of the traditional system.

In order to improve the vehicle economy of electric vehicles, this paper first analyzes the energy-saving mechanism of electric vehicles. Taking the energy consumption of the deceleration process as a starting point, this paper deeply analyzes the energy consumption of the deceleration process under several different control modes by the test data, so as to obtain two principles that should be followed in energy-saving control strategy. Then, an intelligent deceleration energy-saving control strategy by getting the forward vehicle information is developed. The overall architecture of the control strategy consists of three parts: information processing, target calculation and torque control. The first part is mainly to obtain the forward vehicle information from the perception systems, and the user's habits information from big data, and this information is processed for the next part.

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.

The purpose of this study is to evaluate the impact of two-stage pilot injection parameters on the combustion and emissions of pilot diesel compression ignition natural gas (CING) engine at low load. Experiments were performed using a diesel/natural gas dual-fuel engine, which was modified from a six-cylinder diesel engine. The effect of injection timing and injection pressure of two-stage pilot diesel were analyzed in order to reduce both the fuel consumption and total hydrocarbon (HC) and carbon monoxide (CO) emissions under low load conditions. The results indicate that, because injection timing can determine the degree of pilot diesel stratification, in-cylinder thermodynamic state, and the available mixing time prior to the combustion, the combustion process can be controlled and optimized through adjusting injection timing.

Minimum energy consumption with maximum comfort driving experience define the ideal human mobility. Recent technological advances in most Advanced Driver Assistance Systems (ADAS) on electric vehicles not only present a significant opportunity for automated eco-driving but also enhance the safety and comfort level. Understanding driving styles that make the systems more human-like or personalized for ADAS is the key to improve the system comfort. This research focuses on the personalized and green adaptive cruise control for intelligent electric vehicle, which is also known to be MyEco-ACC. MyEco-ACC is based on the optimization of regenerative braking and typical driving styles. Firstly, a driving style model is abstracted as a Hammerstein model and its key parameters vary with different driving styles. Secondly, the regenerative braking system characteristics for the electric vehicle equipped with 4-wheel hub motors are analyzed and braking force distribution strategy is designed.

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.

Vehicle yaw stability control (YSC) can actively adjust the working state of the chassis actuator to generate a certain additional yaw moment for the vehicle, which effectively helps the vehicle maintain good driving quality under strong transient conditions such as high-speed turning and continuous lane change. However, the traditional YSC pursues too much driving stability after activation, ignoring the difference of multi-objective requirements of yaw maneuverability, actuator energy consumption and other requirements in different vehicle stability states, resulting in the decline of vehicle driving quality. Therefore, a vehicle yaw stability model predictive control strategy for dynamic and multi-objective requirements is proposed in this paper. Firstly, the unstable characteristics of vehicle motion are analyzed, and the nonlinear two-degree-of-freedom vehicle dynamics models are established respectively.