Search Results

Due to the high cost of torque sensors, a calculation model of transient torque is required for real-time coordinating control purpose, especially in hybrid electric powertrains. This paper presents a feedforward calculation method based on mean value model of turbocharged non-EGR diesel engines. A fitting variable called fuel coefficient is defined in an affine relation between brake torque and fuel mass. The fitting of fuel coefficient is simplified to depend only on three variables (engine speed, boost pressure, injected fuel mass). And a two-layer feedforward neural network is utilized to fit the experimental data. The model is validated by load response test and ETC (European Transient Cycle) transient test. The RMSE (root mean square error) of the brake torque is less than 3%.

Electromagnetic Valve Actuation (EVA) is considered to be a potential substitute of conventional valvetrains for automotive engines. However, valve quiet-seating (soft-landing) is difficult to be achieved. The EVA system and hence its’ mathematic model is nonlinear. Therefore, when linear control is used for EVA, firstly, the model has to be linearized at an equilibrium point through Taylor expansion. Consequently, the linearized model and control are valid only for a small range around the equilibrium point. This paper presents a control strategy for the whole transition of EVA, which combines exact linearization with Linear Quadratic Regulator (LQR). Firstly, the nonlinear EVA model is transformed to be linear in a new coordinate by using exact linearization, so the nonlinear model is not involved. Then the exact-linearized model is used for the EVA control with LQR.

A new dynamic tire model for estimating the longitudinal/lateral road-tire friction force was derived in this paper. The model was based on the previous Dugoff tire model, in consideration of its drawback that it does not reflect the actual change trend that the tire friction force decreases with the increment of wheel slip ratio when it enters into the nonlinear region. The Dugoff model was modified by fitting a series of tire force data and compared with the commonly used Magic Formula model. This new dynamic friction model is able to capture accurately the transient behavior of the friction force observed during pure longitudinal wheel slip, lateral sideslip and combined slip situation. Simulation has been done under different situations, while the results validate the accuracy of the new tire friction model in predicting tire/road friction force during transient vehicle motion.

The electromagnetic regenerative suspension has attracted much attention recently due to its potential to improve ride comfort and handling stability, at the same time recover kinetic energy which is typically dissipated in traditional shock absorbers. The key components of a ball-screw regenerative suspension system are a motor, a ball screw and a nut. For this kind of regenerative suspension, its damping character is determined by the motor's torque-speed capacity, which is different from the damping character of the traditional shock absorber. Therefore, it is necessary to establish a systematic approach for the parameter matching of ball-screw regenerative suspension, so that the damping character provided by it can ensure ride comfort and handling stability. In this paper, a 2-DOF quarter vehicle simulation model with regenerative suspension is constructed. The effects of the inertia force on ride comfort and handling stability are analyzed.

Tracked vehicles are widely used for agriculture, construction and many other areas. Due to high emissions, hybrid electric driveline has been applied to tracked vehicles. The hybrid powertrain design for the tracked vehicle has been researched for years. Different from wheeled vehicles, the tracked vehicle not only requires high mobility while straight driving, but also pursues strong steering performance. The paper takes the hybrid track-type dozers (TTDs) as an example and proposes an optimal design of a novel power-split powertrain for TTDs. The commercial hybrid TTD usually adopts the series hybrid powertrain, and sometimes with an extra steering mechanism, which has led to low efficiency and made the structure more complicated. The proposed three-planetary-gear power-split hybrid powertrain can overcome the problems above by utilizing the characteristics of planetary gear sets.

An energy management strategy is needed to optimally allocate the driver's power demands to different power sources in the fuel cell hybrid vehicles. The driver's power demand is modelled as a Markov process in which the transition probabilities are estimated on the basis of the observed sample paths. The Markov Decision Process (MDP) theory is applied to design a stochastic energy management strategy for fuel cell hybrid vehicles. This obtained control strategy was then tested on a real time simulation platform of the fuel cell hybrid vehicles. In comparison to the other 3 strategies, the constant bus voltage strategy, the static optimization strategy and the dynamic programming strategy, simulations in the Beijing bus driving cycle demonstrate that the obtained stochastic energy management strategy can achieve better performance in fuel economy in the same demand of dynamic.

This paper has designed a real time control algorithm to use ISG motor actively compensate the torque ripple produced by the engine, to reduce torsional vibration. This paper consists of 3 parts. In the first section, this paper has introduced the research object and its modification for experiments. Then the development of control strategy is presented. The engine dynamic model is built, and real-time control with a feedforward unit and a feedback unit is derived. Encoder and cylinder pressure is used for engine torque estimator. Then the ISG motor output the counter-waveform to make the overall output smooth. In order to verify the effectiveness of the control strategy, the final section has established a test bench, where two experiments are carried out. One of the experimental conditions is to set the engine at a constant operating point, while the other is to crank the engine from 0 rpm to idle speed with ISG motor.

The traditional vacuum booster is gradually replaced by Brake-by-Wire system (BBW) in modern passenger car, especially Electric Vehicle (EV). Some mechanical and hydraulic components are replaced by electronic components in Brake-by-Wire system. Using BBW system in modern passenger vehicles can not only improve the automotive safety performance, reliability and stability, but also promote vehicle maneuverability, comfort, fuel economy and environmental protection. Although vehicle's braking performance is greatly improved by using BBW, the system will inevitably consume some energy of the vehicle power supply, thus introducing unexpected drawback in comparison with the traditional vacuum assist braking system, since it doesn't need any electric power. Therefore, the analysis of energy consumption on typical main cylinder booster based BBW system under typical driving cycles will contribute to advanced design of current advanced braking system.

Safety of buses is crucial because of the large proportion of the public transportation sector they constitute. To improve bus safety levels, especially to avoid driver error, which is a key factor in traffic accidents, we designed and implemented an intelligent bus called iBus. A robust system architecture is crucial to iBus. Thus, in this paper, a novel self-driving system architecture with improved robustness, such as to failure of hardware (including sensors and controllers), is proposed. Unlike other self-driving vehicles that operate either in manual driving mode or in self-driving mode, iBus offers a dual-control mode. More specifically, an online hot standby mechanism is incorporated to enhance the reliability of the control system, and a software monitor is implemented to ensure that all software modules function appropriately. The results of real-world road tests conducted to validate the feasibility of the overall system confirm that iBus is reliable and robust.

The ability of actively adjusting attitude provides a great advantage for those vehicles used in special environments such as off-road environment with extreme terrains and obstacles. It can improve vehicles’ stability and performance. This paper proposes an attitude control system for realizing the active attitude adjustment and vehicle motion control in the same time. The study is based on a vehicle with six wheel independent drive and six independent suspensions (6WIDIS), which is a kind of unmanned vehicle with six in-wheel drives and six independent hydro pneumatic suspensions. With the hydro- pneumatic suspensions, the vehicle’s attitude can be actively adjusted. This paper develops a centralized- distributed control strategy with attitude information obtained by multi-sensor fusion, which can coordinate the complex relationship among the six wheels and suspensions. The attitude control system consists of three parts.

In the context of carbon neutrality, ammonia is considered a zero-carbon fuel with potential applications in the transportation sector. However, its high ignition energy, low flame speed, and high natural temperature, indicative of low reactivity, make it challenging to be applied as a sole fuel in engines. In such a scenario, the use of another zero-carbon and highly reactive fuel, hydrogen, becomes necessary to enhance the combustion of ammonia. Furthermore, jet ignition, a method known for improving engine combustion performance, may also hold potential for enhancing the combustion performance of ammonia engines. To explore the applicability of jet ignition in engines, this study conducted experimental research on a single-cylinder engine. Two ignition methods were employed: passive jet ignition of premixed ammonia-hydrogen at a compression ratio of 11.5, and active jet ignition of pure ammonia using hydrogen jet flame at a compression ratio of 17.3.

In this paper, the differences between multi-hole and single-hole spray contour under the same conditions were compared by using high-speed photography. The difference between the contour area of multi-hole and that of single-hole spray was used as a parameter to describe the degree of spray collapse. Three dimensionless parameters (i.e. degree of superheat, degree of undercooling, and nozzle pressure ratio) were applied to characterize inside-nozzle thermodynamic, outside-nozzle thermodynamic and kinetic factors, respectively. In addition, the relationship between the three dimensionless parameters and the spray collapse was analyzed. A semi-empirical equation was proposed for evaluation of the degree of collapse based on dimensionless parameters of flash and non-flash boiling sprays respectively.

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.

Traffic congestions are increasingly severe in urban areas, especially at the merging areas of the ramps and the arterial roads. Because of the complex conflict relationship of the vehicles in ramps and arterial roads in terms of time-spatial constraints, it is challenging to coordinate the motion of these vehicles, which may easily cause congestions at the merging areas. The connected and automated vehicles (CAVs) provides potential opportunities to solve this problem. A centralized merging control method for CAVs is proposed in this paper, which can organize the traffic movements in merging areas efficiently and safely. In this method, the merging control model is built to formulate the vehicle coordination problem in merging areas, which is then transformed to the discrete nonlinear optimization form. A simulation model is built to verify the proposed method.

The internal combustion engine and motor should be controlled coordinately to meet the demand of smooth power transfer and good drivability especially during transient conditions for parallel hybrid powertrain system. This paper presents the essential technology of how to estimate the engine torque by the measurement and processing of instantaneous crankshaft speed. One multi-injection gasoline engine and one turbocharged diesel engine are selected to manifest the algorithm of engine torque estimation and the experiments show fairly good results for both engines. Consequently an engine torque sensor can be easily calibrated and applied to feedback engine torque in coordinating control.

Due to the potential on decreasing fuel consumption and design flexibility, parallel configurations are widely used for hybrid electric vehicles (HEVs). However, the fuel economy and economic profitability of parallel HEVs for heavy-duty truck applications under Chinese driving conditions still need to be investigated. It is uneasy to improve the fuel economy of parallel HEVs with a single electric motor from control perspective only. In this article, the battery size of the architecture is optimized by using the dynamic programming (DP) approach, based on a dynamic degradation model of the LiFePO4 battery. Moreover, based on the DP results, a near-optimal control strategy of the hybrid powertrain system for online application is proposed. Finally, with two economic assumptions, the initial costs, operation costs, and payback periods are obtained in a total cost of ownership framework perspective.

Batteries are exposed to dynamic load during vehicle driving. It is significant to clarify the load input of the battery system during vehicle driving for battery pack structural design and optimization. Currently, bolt connection is mostly applied for battery pack constraint to vehicle, as well as for module assembly inside the pack. However, accurate bolt load is always difficult to obtain, while directly force measurement is expensive and time consuming in engineering. In this paper, a precise data driven model based on Elman neural network is established to identify the dynamic bolt loads of the battery pack, using tested acceleration data near bolts. The dynamic bolt force data is measured at the same time with the acceleration data during vehicle running in different driving conditions, utilizing customized bolt force sensors.

Gasoline particulate filter (GPF) is considered a suitable solution to meet the increasingly stringent particle number (PN) regulations for both gasoline direct injection (GDI) and multi-port fuel injection (MPI) engines. Generally, GDI engines emit more particulate matter (PM) and PN. In recent years, GDI engines have gained significant market penetration in the automobile industry owing to better fuel economy and drivability. In this study, an accelerated ash loading method was tested by doping lubricating oil into the fuel for a GDI engine. Emission tests were performed at different ash loads with different driving cycles and GPF combinations. The results showed that the GPF could significantly reduce particle emissions to meet the China 6 regulation. With further ash loading, the filtration efficiency increased above 99% and the effects on fuel consumption and backpressure were found to be limited, even with an ash loading of up to 50 g/l.

Gasoline direct injection (GDI) engines have been developed rapidly in recent years, driven by stringent legislative requirements on vehicle fuel efficiency and emissions. However, one challenge facing GDI is the formation of particulate emissions, particularly with the presence of injector tip deposits. The Chinese market features some gasoline fuels that contain no detergent additives and are prone to deposit formation, which can affect engine performance and emissions. The use of detergent additives to mitigate the formation of injector deposits in a GDI engine was investigated in this study by testing a 1.5L turbocharged GDI engine available in the Chinese market. The engine was operated both on base gasoline and on gasoline dosed with detergent additives to evaluate the effect on injector deposit formation and engine performance and emissions.

High boost and direct injection are effective ways for energy saving in gasoline engines. However, the occurrence of super-knock at high load has become a main obstacle for further improving power density and fuel economy. It has been known that super-knock can be induced by pre-ignition, and oil droplet auto-ignition is found to be one of the possible mechanisms. In this study, experiments were conducted in a single-cylinder thermal research engine (TRE), in which different types of oil and surrogates were directly injected into the cylinder and then led to pre-ignition and super-knock. The effect of oil injection timing, oil injection quantity, different gasoline and different oil were tested. All the oil in this work could induce pre-ignition, even though their combustion phasing was much later than that in the case of n-hexadecane.