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Bushing elasticity is one of the most important compliance factors that significantly influence driving behavior. The deformations of the bushings change the wheel orientations under external forces. Another important factor of bushing compliance is to provide a comfortable driving experience by isolating the vibrations from road irregularities. However, the driving comfort and driving dynamics are often in conflict and need to be balanced in terms of bushing compliance design. Specifically, lateral force steer and brake force steer are closely related to safety and stability and comprises must be minimized. The sensitivity analysis helps engineers to understand the critical bushing for certain compliance attributes, but optimal balancing is complicated to understand. The combination of individual bushing stiffness must be carefully set to achieve an acceptable level of all the attributes.

The automotive industry continues to increase the utilization of computer-aided engineering. This put demands on finding reliable objective measures that correlate to subjective driver assessments on driving stability performance. However, the drivers’ subjective perception of driving stability can be difficult to quantify objectively, especially on test tracks where the wind conditions cannot be controlled. The advancement in driving simulator technology may enable evaluation of driving stability with high repeatability. The purpose of this study is to correlate the subjective assessment of driving stability to reliable objective measures and to evaluate the usefulness of a driving simulator for the subjective assessment. Two different driver clinic studies were performed in a state-of-the-art driving simulator. The first study included 38 drivers (professional, experienced and common drivers) and focused on crosswind gust sensitivity.

Heavy-duty vehicles are primarily powered by diesel fuel, emitting CO2 emissions regardless of the exhaust after-treatment system. Contrastingly, a hydrogen engine has the potential to decarbonize the transportation sector as hydrogen is a carbon free, renewable fuel. In this study, a multi-physics 1D simulation tool (GT-Power) is used to model the gas exchange process and performance prediction of a two-stroke hydrogen engine. The aim is to establish a maximum torque-level for a four-stroke hydrogen engine and then utilize different methods for two-stroke modeling to achieve similar torque by optimizing the gas exchange process. A camless engine is used as base, enabling the flexibility to utilize approximately square valve lift profiles. The preliminary step is the GT-Power model validation, which has been done using diesel and hydrogen engines (single-cylinder heavy-duty) experiments at different operating points (871 rpm, 1200 rpm, 1259 rpm, and 1508 rpm).

An electrically heated catalyst (EHC) in the three-way catalyst (TWC) aftertreatment system of a gasoline internal combustion engine (ICE) provides cold engine start exhaust pollutant emission reduction potential. The EHC can be started before switching on the ICE, thereby offering the possibility to pre-heat (PRH) the TWC, in the absence of exhaust flow. The EHC can also provide post engine start heat (PSH) when the heat is accompanied by exhaust mass flow over the TWC. A mixed heating strategy (MXH) comprises both PRH and PSH. All three strategies are evaluated under a range of engine start variations using an ICE-exhaust aftertreatment (EATS) simulation framework. It is driven by an engine speed-torque requested trace, with an engine-out emissions model focused on cold-start, engine heating and catalyst heating engine measures and a physics- based EATS with EHC model.

Squeak and rattle (S&R) are nonstationary annoying and unwanted noises in the car cabin that result in considerable warranty costs for car manufacturers. Introduction of cars with remarkably lower background noises and the recent emphasis on electrification and autonomous driving further stress the need for producing squeak- and rattle-free cars. Automotive manufacturers use several road disturbances for physical evaluation and verification of S&R. The excitation signals collected from these road profiles are also employed in subsystem shaker rigs and virtual simulations that are gradually replacing physical complete vehicle test and verification. Considering the need for a shorter lead time and the introduction of optimisation loops, it is necessary to have efficient and inclusive excitation load cases for robust S&R evaluation.

Bus drivers are a group at risk of often suffering from musculoskeletal problems, such as low-back pain, while bus passengers on the last-row seats experience accelerations of high values. In this paper, the contribution of K-seat in decreasing the above concern is investigated with a detailed simulation study. The K-seat model, a seat with a suspension that functions according to the KDamper concept, which combines a negative stiffness element with a passive one, is benchmarked against the conventional passive seat (PS) in terms of comfort when applied to different bus users’ seats. More specifically, it is tested in the driver’s and two different passengers’ seats, one from the rear overhang and one from the middle part. For the benchmark shake, both are optimized by applying excitations that correspond to real intercity bus floor responses when it drives over a real road profile.

The automotive trends of vehicles with lower aerodynamic drag and more powerful drivetrains have caused increasing concern regarding stability issues at high speeds, since more streamlined bodies show greater sensitivity to crosswinds. This is especially pronounced for high vehicles, such as sports utility vehicles. Besides, the competitiveness in the automotive industry requires faster development times and, thus, a need to evaluate the high speed stability performance in an early design phase, preferable using simulation tools. The usefulness of these simulation tools partly relies on realistic boundary conditions for the wind and quantitative measures for assessing stability without the subjective evaluation of experienced drivers. This study employs an on-road experimental measurements setup to define relevant wind conditions and to find an objective methodology to evaluate high speed stability.

The potential of 48V Mild Hybrid is promising in meeting the present and future CO2 legislations. There are various system layouts for 48V hybrid system including P0, P1, P2. In this paper, P2 architecture is used to investigate the effects of water injection benefits in a mild hybrid system. Electrification of the conventional powertrain uses the benefits of an electric drive in the low load-low speed region where the conventional SI engine is least efficient and as the load demand increases the IC Engine is used in its more efficient operating region. Engine downsizing and forced induction trend is popular in the hybrid system architecture. However, the engine efficiency is limited by combustion knocking at higher loads thus ignition retard is used to avoid knocking and fuel enrichment becomes must to operate the engine at MBT (Maximum Brake Torque) timing; in turn neutralizing the benefits of fuel savings by electrification.

Homogeneous lean combustion (HLC) can be utilized to substantially improve spark ignited (SI) internal combustion engine efficiency. Higher efficiency is vital to enable clean, efficient and affordable propulsion for the next generation light duty vehicles. More research is needed to ensure robustness, fuel efficiency/NOx trade-off and utilization of HLC. Utilization can be improved by expanding the HLC operating window to higher engine torque domains which increases impact on real driving. The authors have earlier assessed boosted HLC operation in a downsized two-litre engine, but it was found that HLC operation could not be achieved above 15 bar NMEP due to instability and knocking combustion. The observation led to the conclusion that there exists a lean load limit. Therefore, further experiments have been conducted in a single cylinder research DISI engine to increase understanding of high load lean operation.

The various factors that affect ride comfort, including noise, vibrations and harshness (NVH) have been in focus in many research studies due to an increasing demand in ride comfort in the automotive industry. Vibrations have been highlighted as an important contribution to assess and predict overall ride comfort. The purpose of this paper is to present an approach to explain ride comfort with respect to vibration for the seated occupant based on a systematic literature review of previous fundamental research and to relate these results to the application in the contemporary automotive industry. The results from the literature study show that numerous research studies have determined how vibration frequency, magnitude, direction, duration affect human response to vibration. Also, the studies have highlighted how body posture, age, gender and anthropometry affect the human perception of comfort.

This paper presents a model based control strategy aimed to reduce noise and wear during gearshifts in conventional and hybrid Dual Clutch Transmissions (DCT and DCTH) and Automated Manual Transmissions (AMT). The control strategy is based on a newly developed dog teeth position sensor layout at China Euro Vehicle Technology AB (CEVT), a detailed simulation model for gear engagement and already existing speed sensors in the transmission. The details of dog teeth position sensor and simulation model are also presented in this paper. During gear shifting, noise is generated because of impacts between the sleeve teeth and the idler gear dog teeth after speed synchronization. Besides noise, these impacts are also responsible for delaying the completion of shift and contribute to wear in the dog teeth, hence reducing the lifespan of the transmission. The simulation model for gear engagement can simulate these impacts.

48V mild hybrid powertrains are promising technologies for cost-effective compliance with future CO2 emissions standards. Current 48V powertrains with integrated belt starter generators (P0) with downsized engines achieve CO2 emissions of 95 g/km in the NEDC. However, to reach 75 g/km, it may be necessary to combine new 48V powertrain architectures with alternative fuels. Therefore, this paper compares CO2 emissions from different 48V powertrain architectures (P0, P1, P2, P3) with different electric power levels under various driving cycles (NEDC, WLTC, and RTS95). A numerical model of a compact class passenger car with a 48V powertrain was created and experimental fuel consumption maps for engines running on different fuels (gasoline, Diesel, E85, CNG) were used to simulate its CO2 emissions. The simulation results were analysed to determine why specific powertrain combinations were more efficient under certain driving conditions.

Increasing the injection pressure in gasoline direct injection engines has a substantial potential to reduce emissions while maintaining a high efficiency in spark ignition engines. Present gasoline injectors are operating in the range of 20 MPa to 25 MPa. Now there is an interest in higher fuel injection pressures, for instance, around 40 MPa, 60 MPa and even higher pressures, because of its potential for further emission reduction and fuel efficiency improvements. In order to fully utilize the high-pressure fuel injection technology, a fundamental understanding of gasoline spray characteristics is vital to gain insight into spray behavior under such high injection pressures. The understanding achieved may also be beneficial to improve further model development and facilitate the integration of such advanced injection systems into future gasoline engines.

Look ahead information can be used to improve the powertrain’s fuel consumption while efficiently controlling exhaust emissions. A passenger car propelled by a Euro 6d capable diesel engine is studied. In the conventional approach, the diesel powertrain subsystem control is rule based. It uses no information of future load requests but is operated with the objective of low engine out exhaust emission species until the Exhaust After-Treatment System (EATS) light off has occurred, even if fuel economy is compromised greatly. Upon EATS light off, the engine is operated more fuel efficiently since the EATS system is able to treat emissions effectively. This paper presents a supervisory control structure with the intended purpose to operate the complete powertrain using a minimum of fuel while improving the robustness of exhaust emissions.

Due to stricter emission regulations and more environmental awareness, the powertrain systems are moving toward higher fuel efficiency and lower emissions. In response to these pressing needs, new technologies have been designed and implemented by manufacturers. As a result of increasing complexity of the powertrain systems, their control and optimization become more and more challenging. Virtual powertrain calibration, also known as model-based calibration, has been introduced to transfer a part of test bench testing into a virtual environment, and hence considerably reduce time and cost of product development process while increasing the product quality. Nevertheless, virtual calibration has not yet reached its full potential in industrial applications. Volvo Penta has recently developed a virtual test cell named VIRTEC, which is used in an ongoing pilot project to meet the Stage V emission standards.

The present paper aims at developing an innovative procedure to create a one-dimensional (1D) real-time capable simulation model for a heavy-duty diesel engine. The novelty of this approach is the use of the top-level engine configuration, test cell measurement data, and manufacturer maps as opposite to common practice of utilizing a detailed 1D engine model. The objective is to facilitate effective model adjustments and hence further increase the application of Hardware-in-the-Loop (HiL) simulations in powertrain development. This work describes the development of Fast Running Model (FRM) in GT-SUITE simulation software. The cylinder and gas-path modeling and calibration are described in detail. The results for engine performance and exhaust emissions produced satisfactory agreement with both steady-state and transient experimental data.

In engine research and development there are often different engine parameters that produce similar effects on the end-point results. When calibrating modern engines, a huge number of parameters needs to be set, which also includes compensation parameters for model imperfections. In this context, simpler, more robust, and physically based models should be beneficial both for calibration work load and powertrain performance. In this study, we present an experimental methodology that uses intermediate (“intrinsic”) variables instead of engine parameters. By using simple thermodynamic models, the engine parameters EGR, IVC, and PBoost could be translated into oxygen concentration, temperature and gas density at the start of injection. The reason for this transformation of data is to “move” the Design of Experiment (DoE) closer to the situation of interest (i.e. the combustion) and to be able to construct simpler and more physically based models.

A two-state forward dynamic programming algorithm is evaluated in a series hybrid drive-train application with the objective to minimize fuel consumption when look-ahead information is available. The states in the new method are battery state-of-charge and engine speed. The new method is compared to one-state dynamic programming optimization methods where the requested generator power is found such that the fuel consumption is minimized and engine speed is given by the optimum power-speed efficiency line. The other method compared is to run the engine at a given operating point where the system efficiency is highest, finding the combination of engine run requests over the drive-cycle that minimizes the fuel consumption. The work has included the engine torque and generator power as control signals and is evaluated in a full vehicle-simulation model based on the Volvo Car Corporation VSIM tool.

Many technological developments in automobile powertrains have been implemented in order to increase efficiency and comply with emission regulations. Although most of these technologies show promising results in official fuel economy tests, their benefits in real driving conditions and real driving emissions can vary significantly, since driving profiles of many drivers are different than the official driving cycles. Therefore, it is important to assess these technologies under different driving conditions and this paper aims to offer an overall perspective, with a numerical study in simulations. The simulations are carried out on a compact passenger car model with eight powertrain configurations including: a naturally aspirated spark ignition engine, a start-stop system, a downsized engine with a turbocharger, a Miller cycle engine, cylinder deactivation, turbocharged downsized Miller engine, a parallel hybrid electric vehicle powertrain and an electric vehicle powertrain.

The current trend toward more fuel efficient vehicles with lower emission levels has prompted development of new combustion techniques for use in gasoline engines. Stratified combustion has been shown to be a promising approach for increasing the fuel efficiency. However, this technique is hampered by drawbacks such as increased particulate and standard emissions. This study attempts to address the issues of increased emission levels by investigating the influence of high frequency ionizing ignition systems, 350 bar fuel injection pressure and various tumble levels on particulate emissions and combustion characteristics in an optical SGDI engine operated in stratified mode on isooctane. Tests were performed at one engine load of 2.63 bar BMEP and speed of 1200 rpm. Combustion was recorded with two high speed color cameras from bottom and side views using optical filters for OH and soot luminescence.