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Lean-burn hydrogen internal combustion engines are a good option for future transportation solutions since they do not emit carbon-dioxide and unburned hydro-carbons, and the emissions of nitric-oxides (NOx) can be kept low. However, under lean-burn conditions the combustion duration increases, and the combustion stability decreases, leading to a reduced thermal efficiency. Turbulent jet ignition (TJI) can be used to extend the lean-burn limit, while decreasing the combustion duration and improving combustion stability. The objective of this paper is to investigate the feasibility of a passive pre-chamber TJI system on a heavy-duty hydrogen engine under lean-burn conditions using CFD modelling. The studied concept is mono-fuel, port-fuel injected, and spark ignited in the pre-chamber. The overall design of the pre-chamber is discussed and the effect of design parameters on the engine performance are studied.

A model-based control approach is proposed to give proper reference for the feed-forward combustion control of Partially Pre-mixed Combustion (PPC) engines. The current study presents a simplified first principal model, which has been developed to provide a base estimation of the ignition properties. This model is used to describe the behavior of a single-cylinder heavy-duty diesel engine fueled with a mix of bio-butanol and n-heptane (80vol% bio-butanol and 20 vol% n-heptane). The model has been validated at 8 bar gross Indicated Mean Effective Pressure (gIMEP) in PPC mode. Inlet temperature and pressure have been varied to test the model capabilities. First the experiments were conducted to generate reference points with BH80 under PPC conditions. And then CFD simulations were conducted to give initial parameter set up, e.g. fuel distribution, zone dividing, for the multi-zone model.

This paper focusses on the application of bioalcohols (ethanol and butanol) derived from seaweed in Heavy-Duty (HD) Compression Ignition (CI) combustion engines. Seaweed-based fuels do not claim land and are not in competition with the food chain. Currently, the application of high octane bioalcohols is limited to Spark Ignition (SI) engines. The Reactivity Controlled Compression Ignition (RCCI) combustion concept allows the use of these low carbon fuels in CI engines which have higher efficiencies associated with them than SI engines. This contributes to the reduction of tailpipe CO2 emissions as required by (future) legislation and reducing fuel consumption, i.e. Total-Cost-of-Ownership (TCO). Furthermore, it opens the HD transport market for these low carbon bioalcohol fuels from a novel sustainable biomass source. In this paper, both the production of seaweed-based fuels and the application of these fuels in CI engines is discussed.

Diesel spray mixture formation is investigated at target conditions using multiple diagnostics and laboratories. High-speed Particle Image Velocimetry (PIV) is used to measure the velocity field inside and outside the jet simultaneously with a new frame straddling synchronization scheme. The PIV measurements are carried out in the Engine Combustion Network Spray A target conditions, enabling direct comparisons with mixture fraction measurements previously performed in the same conditions, and forming a unique database at diesel conditions. A 1D spray model, based upon mass and momentum exchange between axial control volumes and near-Gaussian velocity and mixture fraction profiles is evaluated against the data.

Green zones are challenging problems for the thermal management systems of hybrid vehicles. This is because within the green zone the engine is turned off, and the only way to keep the aftertreatment system warm is lost. This means that there is a risk of leaving the green zone with a cold and ineffective aftertreatment system, resulting in high emissions. A thermal management strategy that heats the aftertreatment system prior to turning off the engine, in an optimal way, to reduce the NOx emissions when the engine is restarted, is developed. The strategy is also used to evaluate under what conditions pre-heating is a suitable strategy, by evaluating the performance in simulations using a model of a heavy-duty diesel powertrain and scenario designed for this purpose.

Butanol is an attractive alternative fuel by virtue of its renewable source and low sooting tendency. In this paper, three butanol isomers (n-butanol, isobutanol, and tert-butanol) were induced via port injection respectively and n-heptane was directly injected into the cylinder to investigate reactivity controlled compression ignition in a heavy-duty diesel engine. This work evaluates the potential of applying butanol as low reactivity fuel and the effects of reactivity gradient on combustion and emission characteristics. The experiments were performed from low load to medium-high load. Due to the different reactivities among the butanol isomers, the exhaust gas recirculation rate and the direct injection strategy were varied for a specific butanol isomer and testing load. Particularly, isobutanol/n-heptane can be operated with single direct injection and no exhaust gas recirculation up to medium load due to the high octane rating.

Multiple injection strategies are commonly used in conventional Diesel engines due to the flexibility for optimizing heat-release timing with a consequent improvement in fuel economy and engine-out emissions. This is also desirable in low-temperature combustion (LTC) engines since it offers the potential to reduce unburned hydrocarbon and CO emissions. To better utilize these benefits and find optimal calibrations of split injection strategies, it is imperative that the fundamental processes of multiple injection combustion are understood and computational fluid dynamics models accurately describe the flow dynamics and combustion characteristics between different injection events. To this end, this work is dedicated to the identification of suitable methodologies to predict the multiple injection combustion process.

Rubber is a non-linear viscoelastic material which properties depend upon several factors. In a tire two of these factors, namely the temperature and excitation frequency, are significantly influenced by the vehicle operating conditions. In the past years, applied research studied how rubber viscoelastic characteristics affect structural and frictional tire properties. The present study focuses on how these effects interact with the vehicle handling response. Based on state of the art theory of friction, structural properties of rubber and on experimental evidence, the dependency of key tire parameters on temperature and rolling speed is established. These results are then used in combination with a single-track vehicle model to assess their impact on key vehicle parameters; as an example, the understeer coefficient, yaw resonance peak / damping and maximum acceleration are studied.

CO2 regulations on heavy-duty transport are introduced in essentially all markets within the next decade, in most cases in several phases of increasing stringency. To cope with these mandates, developers of engines and related equipment are aiming to break new ground in the fields of combustion, fuel and hardware technologies. In this work, a novel diesel fuel injector, Delphi’s DFI7, is utilized to experimentally investigate and compare the performance of ramped injection rates versus traditional square fueling profiles. The aim is specifically to shift the efficiency and NOx tradeoff to a more favorable position. The design of experiments methodology is used in the tests, along with statistical techniques to analyze the data. Results show that ramped and square rates - after optimization of fueling parameters - produce comparable gross indicated efficiencies.

N-butanol, as a biomass-based renewable fuel, has many superior fuel properties. It has a higher energy content and cetane number than its alcohol competitors, methanol and ethanol. Previous studies have proved that n-butanol has the capability to achieve lower emissions without sacrifice on thermal efficiency when blended with diesel. However, most studies on n-butanol are limited to low blending ratios, which restricts the improvement of emissions. In this paper, 80% by volume of n-butanol was blended with 20% by volume of n-heptane (namely BH80). The influences of various engine parameters (combustion phasing, EGR ratio, injection timing and intake pressure, respectively) on its combustion and emission characteristics are tested at different loads. The results showed that when BH80 uses more than 40% EGR, the emitted soot and nitrogen oxides (NOx) emissions are below the EURO VI legislation.

In the hybrid brake system of electric vehicle, due to the limitation of the motor braking force when the motor is at high speed and the failure of the regenerative braking force when the motor is at low speed, there are three transitional conditions in hybrid braking: the hydraulic brake system intervenes the braking, the hydraulic brake system withdraws the braking and the regenerative braking force withdraws the braking. Due to the response speed of the hydraulic system is slower than that of the motor, there is a large braking impact (the derivative of braking deceleration) in the transitional conditions of hybrid braking, which deteriorates the smoothness and comfort in braking. Aiming at the impact caused by the poor cooperation between the hydraulic braking force and the motor braking force, a coordinated strategy of double closed-loop feedback and motor force correction is proposed in this paper.

In the process of ABS control, the Anti-lock braking system (ABS) of the vehicle adjusts the wheel cylinder brake pressure through the hydraulic actuator so as to control the movement of the wheel. The high-speed on-off valve (HSV) is the key components of the Anti-lock braking system. HSV affects the performance of the hydraulic actuator and the valve response characteristics affects the Anti-lock braking system pressure response as well as braking effect. In this paper, the electromagnetic field theory and flow field theory of HSV are analyzed, and simulation analysis of electromagnetic field characteristics of HSV is done by ANSYS. Combined with the ANSYS analysis results, a precise physical model of HSV is constructed in AMESim. Meanwhile, the valve response characteristics are analyzed. Moreover, the influence of different wheel cylinder diameter and PWM carrier frequency on hydraulic braking force characteristics are analyzed.

The accepted model of conventional diesel combustion [1] assumes a rich premixed flame slightly downstream of the maximum liquid penetration. The soot generated by this rich premixed flame is burnt out by a subsequent diffusion flame at the head of the jet. Even in situations in which the centre of combustion (CA50) is phased optimally to maximize efficiency, slow late stage combustion can still have a significant detrimental impact on thermal efficiency. Data is presented on potential late-stage combustion improvers in a EURO VI compliant HD engine at a range of speed and load points. The operating conditions (e.g. injection timings, EGR levels) were based on a EURO VI calibration which targets 3 g/kWh of engine-out NOx. Rates of heat release were determined from the pressure sensor data. To investigate late stage combustion, focus was made on the position in the cycle at which 90% of the fuel had combusted (CA90). An EN590 compliant fuel was tested.

Premixed Charge Compression Ignition concepts are promising to reduce NOx and soot simultaneously and keeping a high thermal efficiency. Partially premixed combustion is a single fuel variant of this new combustion concepts applying a fuel with a low cetane number to achieve the necessary long ignition delay. In this study, multiple injection strategies are studied in the partially premixed combustion approach to reach stable combustion and ultra-low NOx and soot emission at 15.5 bar gross indicated mean effective pressure. Three different injection strategies (single injection, pilot-main injection, main-post injection) are experimentally investigated on a heavy duty compression ignition engine. A fuel blend (70 vol% n-butanol and 30 vol% n-heptane) was tested. The effects of different pilot and post-injection timing, as well as Exhaust-gas Recirculation rate on different injection strategies investigated.

A contemporary approach for improving and developing the understanding of heavy-duty Diesel engine combustion processes is to use a concerted effort between experiments at well-characterized boundary conditions and detailed, high-fidelity models. In this paper, combustion processes of n-dodecane fuel sprays under heavy-duty Diesel engine conditions are investigated using this approach. Reacting fuel sprays are studied in a constant-volume pre-burn vessel at an ambient temperature of 900 K with three reference cases having specific combinations of injection pressure, ambient density and ambient oxygen concentration (80, 150 & 160 MPa - 22.8 & 40 kg/m3-15 & 20.5% O2). In addition to a free jet, two different walls were placed inside the combustion vessel to study flame-wall interaction.

Automatic lane change of intelligent vehicles is a complex process. Besides of safety, feelings of the driver and passengers during the lane change are also very important. In this paper, a lane change trajectory planner is designed to generate an ideal collision-free trajectory to satisfy the driver’s preference. Various lane changing modes, gentle lane change, general lane change, radical lane change and personalized lane change, are designed to meet the needs of different passengers on vehicles simultaneously. In this paper, the condition of the two-lane change is studied. One vehicle is in front of the ego vehicle at the same lane and one is at the rear of the ego vehicle at the target lane. A trajectory planning method is then established based on constant speed offset and sine curve, vehicle distances and speed difference, etc. The key factors which can reflect drivers’ lane change characteristics are then acquired.

With the development of autonomous vehicle technology, there is an increasing tendency toward the application of intelligent sensors in environment-perception system on autonomous vehicle to assist vehicle in intelligent decision making relevant to autonomous driving. As for environment-perception system, a good track management method serves as the foundation, while multi-target tracking and multi-sensor data fusion are recognized as the key. In this paper, a track management method is proposed to deal with multi-target tracking based on the target-level data of multisource environmental sensors for autonomous vehicle. The track management includes four procedures as following: track initiation; point-track association; track update; track deletion. A modified fast algorithm for data association is applied in the point-track association procedure. Afterwards Kalman filter is implemented to update the track information of target. The algorithm has got through a simulation test.

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.

Target detection is essential to the advanced driving assistance system (ADAS) and automatic driving. And the data fusion of millimeter wave radar and camera could provide more accurate and complete information of targets and enhance the environmental perception performance. In this paper, a method of vehicle and pedestrian detection based on the data fusion of millimeter wave radar and camera is proposed to improve the target distance estimation accuracy. The first step is the targets data acquisition. A deep learning model called Single Shot MultiBox Detector (SSD) is utilized for targets detection in consecutive video frames captured by camera and further optimized for high real-time performance and accuracy. Secondly, the coordinate system of camera and radar are unified by coordinate transformation matrix. Then, the parallel Kalman filter is used to track the targets detected by radar and camera respectively.

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.