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In the port injected Spark Ignition (SI) engine, the single greatest part load efficiency reducing factor are energy losses over the throttle valve. The need for this throttle valve arises from the fact that engine power is controlled by the amount of air in the cylinders, since combustion occurs stoichiometrically in this type of engine. In WEDACS (Waste Energy Driven Air Conditioning System), a technology patented by the Eindhoven University of Technology, the throttle valve is replaced by a turbine-generator combination. The turbine is used to control engine power. Throttling losses are recovered by the turbine and converted to electrical energy. Additionally, when air expands in the turbine, its temperature decreases and it can be used to cool air conditioning fluid. As a result, load of the alternator and air conditioning compressor on the engine is decreased or even eliminated, which increases overall engine efficiency.

Cylinder pressure-based combustion control is widely introduced for passenger cars. Benefits include enhanced emission robustness to fuel quality variation, reduced fuel consumption due to more accurate (multi-pulse) fuel injection, and minimized after treatment size. In addition, it enables the introduction of advanced, high-efficient combustion concepts. The application in truck engines is foreseen, but challenges need to be overcome related to durability, increased system costs, and impact on the cylinder head. In this paper, a new single cylinder pressure sensor concept for heavy-duty Diesel engines is presented. Compared to previous studies, this work focuses on heavy-duty Diesel powertrains, which are characterized by a relatively flexible crank shaft in contrast to the existing passenger car applications.

Homogeneous Charge Compression Ignition (HCCI) combustion technology has demonstrated a profound potential to decrease both emissions and fuel consumption. In this way, the significance of the 2-stroke HCCI engine has been underestimated as it can provide more power stroke in comparison to a 4-stroke engine. Moreover, the mass of trapped residual gases is much larger in a 2-stroke engine, causing higher initial charge temperatures, which leads to easier auto-ignition. For controlling 2-stroke HCCI engines, it is vital to find optimized simulation approaches of HCCI combustion with a focus on ignition timing. In this study, a Computational Fluid Dynamic (CFD) model for a 2-stroke gasoline engine was developed coupled to a semi-detailed chemical mechanism of iso-octane to investigate the simulation capability of the considered chemical mechanism and the effects of different simulation parameters such as the turbulence model, grid density and time step size.

This paper discusses the development and subsequent validation process of generic multi-body models for commercial vehicle combinations. The model is intended for performance assessment and improving of current and future combinations for the European road network. A second goal is to employ the model for the development of driver support systems and active steering strategies for both low speed manoeuvrability and high speed stability. The model is developed in SimMechanics, which is part of the MATLAB/Simulink software. Due to its modularity, one can quickly modify the model to the desired configuration and dimensions; therefore various multi articulation vehicle models can be created. The paper further illustrates the simplified and generic modelling methods used to build particular components such as chassis, tyres or suspension in the multibody domain.

Collision of injected fuel spray against the cylinder liner (wall-wetting) is one of the main hurdles that must be overcome in order for early direct injection Premixed Charge Compression Ignition (EDI PCCI) combustion to become a viable alternative for conventional DI diesel combustion. Preferably, the prevention of wall-wetting should be realized in a way of selecting appropriate (most favorable) operating conditions (EGR level, intake temperature, injection timing-strategy etc.) rather than mechanical modification of an engine (combustion chamber shape, injector replacement etc.). This paper presents the effect of external uncooled EGR (different fraction) on wall-wetting issues specified by two parameters, i.e. measured smoke number (experiment) and liquid spray penetration (model).

In order to solve the problem that in the traditional trilateral positioning algorithm, the final positioning error is large when there is a certain error in the measured three-sided distance, a UWB positioning algorithm based on Back Propagation (BP) neural network is proposed. The algorithm utilizes the fast learning characteristic and the ability of approximating any non-linear mapping of neural network, and realizes the location of the mobile label through the TOA measurement value provided by the base station and the BP neural network. By comparing the traditional trilateral positioning algorithm, the BP neural network algorithm based on four distance inputs and the BP neural network algorithm based on four distance inputs with trilateral positioning coordinates, it can be seen that the positioning error of traditional trilateral positioning algorithm is 30 cm, and the positioning error of the positioning algorithm based on the BP neural network proposed in this paper is 10 cm.

To improve the cold start performance and to reduce the misfire occurrence at cold start, the start-up strategy of total stoichiometric ratio combined with local rich mixture was applied in the study. The effect of injection strategy (the 1st injection timing, 2nd injection timing, 1st and 2nd fuel injection proportion and ignition timing) on the cold start HC emissions in the initial 10 cycles were investigated in a Two stage direct injection (TSDI) gasoline engine. The transient HC and NO emissions in the initial 10 cycles were analyzed, when the fuels are injected in the only 1st cycle and in the followed all cycles. The transient misfiring HC emissions were compared between the single and two-stage injection modes. In addition, the unburned HC (UBHC) emissions in the 1st cycle are compared among the TSDI engine, Gasoline direct injection (GDI) engine, Port fuel injection (PFI) engine and Liquefied petroleum gaseous (LPG) engine at the stoichiometric ratio.

For natural gas (NG)-diesel RCCI, a multi-zonal, detailed chemistry modeling approach is presented. This dual fuel combustion process requires further understanding of the ignition and combustion processes to maximize thermal efficiency and minimize (partially) unburned fuel emissions. The introduction of two fuels with different physical and chemical properties makes the combustion process complicated and challenging to model. In this study, a multi-zone approach is applied to NG-diesel RCCI combustion in a heavy-duty engine. Auto-ignition chemistry is believed to be the key process in RCCI. Starting from a multi-zone model that can describe auto-ignition dominated processes, such as HCCI and PCCI, this model is adapted by including reaction mechanisms for natural gas and NOx and by improving the in-cylinder pressure prediction. The model is validated using NG-diesel RCCI measurements that are performed on a 6 cylinder heavy-duty engine.

In view of the problem of low-frequency (less than 10Hz, such as 0.5Hz, 1.15Hz, 8Hz in this paper) longitudinal vibration exists in a pure electric vehicle, modeling methods of drive-line torsion vibration system are conducted. Firstly, dynamometer test is performed, signals of motor speed and seat rail acceleration are obtained, the frequency characteristics of flutter is determined using the order analysis and time frequency analysis. Then four types of modeling and analysis are investigated facing the drive-line torsion vibration problem, including single model without electromagnetic stiffness, branch model without electromagnetic stiffness, single model considering electromagnetic stiffness and branch model considering electromagnetic stiffness. The results show that, modeling taking into account the electromagnetic stiffness and branches can reflect more low-frequency characteristics helps to reveal the low-frequency longitudinal flutter of the researched electric vehicle.

Torque Vectoring Control for distributed drive electric vehicle is studied. A handling improvement algorithm for normal cornering maneuvers is proposed based on state variable feedback control: Yaw rate feedback together with steer angle feedforward is employed to improve transient response and steady gain of the yaw rate, respectively. According to the feedback coefficient's influence on the transient response, an optimization function is proposed to obtain optimum feedback coefficients under different speeds. After maximum feedforward coefficients under different speeds are obtained from the constraint of the motor exterior characteristic, final feedforward coefficients are calculated according to an optimal steering characteristic. A torque distribution algorithm is presented to help the driver to speed up during the direct yaw moment control.

Prediction and analysis of the thermo-mechanical coupling behavior in friction braking system is very important for the design and application of vehicle brakes, such as brake judder, brake squeal, brake wear, brake cracks, brake fade. This paper aims to establish a macro-structural model of the thermo-mechanical dynamics of the ventilated disc brake with asymmetrical outer and inner disc thickness, taking into account the friction-velocity curve of the disc pad couple acquired by testing. On the basis of finite elements analysis of the model, the predictions of the thermo-mechanical responses of the brake disc are presented, including disc transient temperature field and normal stress in radial, circular and axial directions, disc lateral deformation and disc thickness variation. Numerical predictions of the disc surface temperature and later distortion are compared with experimental measurements obtained by thermocouples and non-contact displacement sensors.

The automatic lane change assist system is an intelligent driving assistance technology oriented to traffic safety, which requires trajectory planning of the lane change maneuver based on the lane change decision. A typical scene of lane change for overtaking is selected, where the front vehicle in the same lane and the rear vehicle in the left lane are deemed to be potential dangerous vehicles through the lane change. Lane change trajectory equation is first established according to the general law of steering wheel angle through lane changes. Based on the relative position, velocity and acceleration information of the dangerous vehicles and the lane change vehicle, motions of these surrounding dangerous vehicles are predicted. At the same time, a multi-objective optimization function is established based on the relative longitudinal safety boundary. The objectives are the minimum safety distance, the lane change time and the front wheel angle.

In this paper, the system identification theory and method using dynamic neural networks are presented, the multilayer feedforward networks employed, the backpropagation with adaptive learning rate algorithms proposed. Finally the comparision of network output with that of the hydrostatic drive system of secondary regulation is given, and output error, sum-squared error et al, or the results that embody the effect of system identification given sine input to it are provided.

The large strain dynamic behavior of brain tissue and silicone gel, a brain substitute material used in mechanical head models, was compared. The non-linear shear strain behavior was characterized using stress relaxation experiments. Brain tissue showed significant shear softening for strains above 1% (approximately 30% softening for shear strains up to 20%) while the time relaxation behavior was nearly strain independent. Silicone gel behaved as a linear viscoelastic solid for all strains tested (up to 50%) and frequencies up to 461 Hz. As a result, the large strain time dependent behavior of both materials could be derived for frequencies up to 1000 Hz from small strain oscillatory experiments and application of Time Temperature Superpositioning. It was concluded that silicone gel material parameters are in the same range as those of brain tissue.

Brake pedal feel characteristic is determined by the structural and kinetic parameters of the components of the brake system. As the servo power component of the brake system, vacuum booster has a significant influence on the brake pedal feel. In this paper, a brake system model for brake pedal feel which has a detail vacuum booster mathematical description is established in the software MATLAB/Simulink. The structure gaps, spring preload, friction force and reaction disc characteristics of vacuum booster are considered in this model. A brake pedal feel bench test under different input velocity and vacuum pressure is completed in order to validate the prediction of the model.

A transparent HSDI CI engine was used together with a high speed camera to analyze the liquid phase spray geometry of the fuel types: Swedish environmental class 1 Diesel fuel (MK1), Soy Methyl Ester (B100), n-Heptane (PRF0) and a gas-to-liquid derivate (GTL) with a distillation range similar to B100. The study of the transient liquid-phase spray propagation was performed at gas temperatures and pressures typical for start of injection conditions of a conventional HSDI CI engine. Inert gas was supplied to the transparent engine in order to avoid self-ignition at these cylinder gas conditions. Observed differences in liquid phase spray geometry were correlated to relevant fuel properties. An empirical relation was derived for predicting liquid spray cone angle and length prior to ignition.

Post-injection strategies prove to be a valuable option for reducing soot emission, but experimental results often differ from publication to publication. These discrepancies are likely caused by the selected operating conditions and engine hardware in separate studies. Efforts to optimize not only engine-out soot, but simultaneously fuel economy and emissions of nitrogen oxides (NOx) complicate the understanding of post-injection effects even more. Still, the large amount of published work on the topic is gradually forming a consensus. In the current work, a Design-of-Experiments (DoE) procedure and regression analysis are used to investigate the influence of various operating conditions on post-injection scheduling and efficacy. The study targets emission reductions of soot and NOx, as well as fuel economy improvements. Experiments are conducted on a heavy-duty compression ignition engine at three load-speed combinations.

Research studies have suggested that changes to the ignition system are required to generate a more robust flame kernel in order to secure the ignition process for the future advanced high efficiency spark-ignition (SI) engines. In a typical inductive ignition system, the spark discharge is initiated by a transient high-power electrical breakdown and sustained by a relatively low-power glow process. The electrical breakdown is characterized as a capacitive discharge process with a small quantity of energy coming mainly from the gap parasitic capacitor. Enhancement of the breakdown is a potential avenue effectively for extending the lean limit of SI engine. In this work, the effect of high-power capacitive spark discharge on the early flame kernel growth of premixed methane-air mixtures is investigated through electrical probing and optical diagnosis.

Millimeter wave automotive radar is one of the most important sensors in the Advanced Driver Assistance System (ADAS) and autonomous driving system, which detects the target vehicles around the ego vehicle via processing transmitted and echo signals. However, the sampling rate of classical radar signal processing methods based on Nyquist sampling theorem is too high and the resolution of range, velocity and azimuth can’t meet the requirement of highly autonomous driving, especially azimuth. In spatial domain, targets are sparse distribution in the detection range of automotive radar. To solve these problems, the algorithm for targets location based on compressed sensing for automotive radar is proposed in this paper. Besides, the feasibility of the algorithm is verified through the simulation experiments of traffic scene. The range-doppler-azimuth model can be used to estimate the distance, velocity and azimuth of the target accurately.

Automotive radar is an important environment perception sensor for advance driving assistance system. It can detect objects around the vehicle with high accuracy and it works in all bad weathers. For traditional automotive radar, it cannot measure the objects’ height. Thus, a manhole cover on the road surface or a guideboard high above the road would be taken erroneously as a non-moving car. In such cases, the adaptive cruise system would decelerate or stop the vehicle erroneously and make the driver uncomfortable. A 3D automotive radar with two-dimensional electronic scanning can measure the targets’ height as well as the targets’ azimuth angle. This paper presents a 79 GHz ultra-wide band automotive 3D imaging radar. Due to the 4 GHz wide bandwidth, the range resolution of this radar can be as small as 3.75 cm.