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The need for efficient space utilization has provided a framework for the design of a 248mm family of torque converters that supports a wide choice of engine and transmission combinations. The axial length of the part and its weight have been substantially reduced while the performance range has been broadened without degradation of efficiency. The new converter operates in an expanded slipping clutch mode. It significantly contributes to the performance and fuel economy improvements of related vehicles. To meet the cost target, the comprehensive lineup and the resulting complexity have required a high level of component interchangeability. During the design phase, the manufacturing core competencies were scrutinized and process redundancies eliminated, both resulting in optimization of material selection and applicable technology.

Flame speed data reported in most literature are acquired in conventional apparatus such as the spherical combustion bomb and counterflow burner, and are limited to atmospheric pressure and ambient or slightly elevated unburnt temperatures. As such, these data bear little relevance to internal combustion engines and gas turbines, which operate under typical pressures of 10-50 bar and unburnt temperature up to 900K or higher. These elevated temperatures and pressures not only modify dominant flame chemistry, but more importantly, they inevitably facilitate pre-ignition reactions and hence can change the upstream thermodynamic and chemical conditions of a regular hot flame leading to modified flame properties. This study focuses on how auto-ignition chemistry affects flame propagation, especially in the negative-temperature coefficient (NTC) regime, where dimethyl ether (DME), n-heptane and iso-octane are chosen for study as typical fuels exhibiting low temperature chemistry (LTC).

This paper presents a method for optimization design of an engine mounting system subjected to some constraints. The engine center of gravity, the mount stiffness rates, the mount locations and/or their orientations with respect to the vehicle can be chosen as design variables, but some of them are given in advance or have limitations because of the packaging constraints on the mount locations, as well as the individual mount rate ratio limitations imposed by manufacturability. A computer program, called DynaMount, has been developed that identifies the optimum design variables for the engine mounting system, including decoupling mode, natural frequency placement, etc.. The degree of decoupling achieved is quantified by kinetic energy distributions calculated for each of the modes. Several application examples are presented to illustrate the validity of this method and the computer program.

Selecting the right transportation platform is challenging, whether it is at a personal level or at an organizational level. In settings where predominantly the functional aspects rule the decision making process, defining the mobility of a vehicle is critical for comparing different offerings and making acquisition decisions. With the advent of intelligent vehicles, exhibiting partial to full autonomy, this challenge is exacerbated. The same vehicle may traverse independently and with greater tolerance for acceleration than human occupied vehicles, while, at the same time struggle with obstacle avoidance. The problem presents itself at the individual vehicle sensing level and also at the vehicle/fleet level. At the sensing and information level, one can be looking at issues of latency, bandwidth and optimal information fusion from multiple sources including privileged sensing. At the overall vehicle level, one focuses more on the ability to complete missions.

With the emergence of intelligent ground vehicles, an objective evaluation of vehicle mobility has become an even more challenging task. Vehicle mobility refers to the ability of a ground vehicle to traverse from one point to another, preferably in an optimal way. Numerous techniques exist for evaluating the mobility of vehicles on paved roads, both quantitatively and qualitatively, however, capabilities to evaluate their off-road performance remains limited. Whereas a vehicle’s off-road mobility may be significantly enhanced with intelligence, it also introduces many new variables into the decision making process that must be considered. In this paper, we present a decision analytic framework to accomplish this task. In our approach, a vehicle’s mobility is modeled using an operator’s preferences over multiple mobility attributes of concern. We also provide a method to analyze various operating scenarios including the ability to mitigate uncertainty in the vehicles inputs.

A continuously variable lift, duration and phase mechanical lift mechanism is described, as applied to the intake valvetrain of a SOHC, 4-valve per cylinder, four-cylinder production engine. Improvements in fuel economy were sought by reduction of pumping losses and improved charge preparation, and optimization of WOT torque was attempted by variation of intake valve closing angle. Adjustment of the mechanism is achieved by movement of the pivot shaft for the rocker arms. The relationship between lift, duration and phase is predetermined at the design stage, and is fixed during operation. There is considerable design flexibility to achieve the envelope of lift curves deemed desirable. The operation of the mechanism is described, as are the development procedure, testing with fixed cams, some cycle simulation, friction testing on a separate rig and dyno testing results for idle, part load and WOT.

Dang Van (Dang Van et al., 1982 and Dang Van, 1993) states that for an infinite lifetime (near fatigue limit), crack nucleation in slip bands may occur at the most unfavorable oriented grains, which are subject to plastic deformation even if the macroscopic stress is elastic. Since the residual stresses in these plastically deformed grains are induced by the restraining effect of the adjacent grains, it is assumed that the residual stresses are stabilized at a mesoscopic level. These stresses are currently approximated by the macroscopic hydrostatic stress defined by the normal stresses to the faces of an octahedral element oriented with the faces symmetric to the principal axis; mathematically they are equal to each other and they are the average of the principal stresses.

The Magma engine concept is characterised by a high compression ratio, central injector combustion system employed in a downsized direct-injection gasoline engine. An advanced boosting system and Miller cycle intake-valve closing strategies are used to control combustion knock while maintaining specific performance. A key feature of the Magma concept is the use of high CR without compromise to mainstream full-load performance levels. This paper focuses on development of the Magma combustion system using a single-cylinder engine, including valve event, air motion and injection strategies. Key findings are that Early Intake Valve Closing (EIVC) is effective both in mitigating knock and improving fuel consumption. A Net Indicated Mean Effective Pressure (NIMEP) equivalent to 23.6 bar Brake Mean Effective Pressure (BMEP) on a multi-cylinder engine has been achieved with a geometric compression ratio of 13:1.

In a gasoline engine, the unswept in-cylinder residual gas and introduction of external EGR is one of the important means of controlling engine raw NOx emissions and improving part load fuel economy via reduction of pumping losses. Since the trapped in-cylinder Residual Gas Fraction (RGF, comprised of both internal, and external) significantly affects the combustion process, on-line diagnosis and monitoring of in-cylinder RGF is very important to the understanding of the in-cylinder dilution condition. This is critical during the combustion system development testing and calibration processes. However, on-line measurement of in-cylinder RGF is difficult and requires an expensive exhaust gas analyzer, making it impractical for every application. Other existing methods, based on measured intake and exhaust pressures (steady state or dynamic traces) to calculate gas mass flowrate across the cylinder ports, provide a fast and economical solution to this problem.

This work analyzes a cantilevered piezoelectric beam device for harvesting energy from the simultaneous rotation and translational vibration of vehicle wheels. The device attaches to the wheel rim so that it displaces tangentially during operation. A lumped-parameter analytical model for the coupled electromechanical system is derived. The device has one natural frequency that is speed-dependent because of centripetal acceleration affecting the total stiffness of the device. Even though the device has one natural frequency, it experiences three resonances as the rotation speed varies. One resonance occurs when the rotation speed coincides with the speed-dependent natural frequency of the device. The other two resonances are associated with excitations from the vibration of the vehicle wheel. The device’s parameters are chosen so that these three resonances occur when the wheel travels near 30 mph, 55 mph, and 70 mph.

Accurate accounting for fresh charge (fuel and air) along with trapped RGF is essential for the subsequent thermodynamic analysis of combustion in gasoline engines as well as for on-line and real-time quantification as relevant to engine calibration and control. Cost and complexity of such techniques renders direct measurement of RGF impractical for running engines. In this paper, an empirically-based approach is proposed for on-line RGF, based on an existing semi-empirical model [1]. The model developed expands the range over which the semi-empirical model is valid and further improves its accuracy. The model was rigorously validated against a well correlated GT-POWER model as well as results from 1D gas exchange model [2]. Overall, using this model, RGF estimation error was within ∼1.5% for a wide range of engine operating conditions. The model will be implemented in Dyno development and calibration at Chrysler Group.

A variety of elastomer mounts are being used for vehicles as isolators/dampers between body and frame, on the engine cradle, etc. These vehicle flexible mounts, made of mainly rubber materials and housed in a metallic tube, are indispensable components affecting the quality of the vehicle ride, noise and vibration. In the auto industry, the usual practice when designing vehicle flexible mounts is to minimally reflect impact considerations in the mount design features. However, in most high-speed vehicle crash events where the mounts fail, the crash responses, including occupant injury severity, are known to be very different from the responses of non-failure cases. Even in low-speed vehicle impact cases, excessive deformation of the flexible mounts could cause significant variance in the compliance of the vehicle acceleration level to the air-bag firing and timing threshold requirements.

Controller Area Network (CAN), the de facto standard for in-vehicle networks, has insufficient security features and thus is inherently vulnerable to various attacks. To protect CAN bus from attacks, intrusion detection systems (IDSs) based on advanced deep learning methods, such as Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN), have been proposed to detect intrusions. However, those models generally introduce high latency, require considerable memory space, and often result in high energy consumption. To accelerate intrusion detection and also reduce memory requests, we exploit the use of Binarized Neural Network (BNN) and hardware-based acceleration for intrusion detection in in-vehicle networks. As BNN uses binary values for activations and weights rather than full precision values, it usually results in faster computation, smaller memory cost, and lower energy consumption than full precision models.

In the dense fabric of urban areas, electric scooters have rapidly become a preferred mode of transportation. As they cater to modern mobility demands, they present significant safety challenges, especially when interacting with pedestrians. In general, e-scooters are suggested to be ridden in bike lanes/sidewalks or share the road with cars at the maximum speed of about 15-20 mph, which is more flexible and much faster than pedestrians and bicyclists. Accurate prediction of pedestrian movement, coupled with assistant motion control of scooters, is essential in minimizing collision risks and seamlessly integrating scooters in areas dense with pedestrians. Addressing these safety concerns, our research introduces a novel e-Scooter collision avoidance system (eCAS) with a method for predicting pedestrian trajectories, employing an advanced Long short-term memory (LSTM) network integrated with a state refinement module.

Future fuel economy targets represent a significant challenge to the automotive industry. While a range of technologies are in research and development to address this challenge, they all bring additional cost and complexity to future products. The most cost effective solutions are likely to be combinations of technologies that in isolation might have limited advantages but in a systems approach can offer complementary benefits. This presentation describes work carried out at Ricardo to explore Intelligent Electrification and the use of Stratified Charge Lean Combustion in a spark ignition engine. This includes a next generation Spray Guided Direct Injection SI engine combustion system operating robustly with highly stratified dilute mixtures and capable of close to 40% thermal efficiency with very low engine-out NOx emissions.

In the development of an FAW SUV, one of the goals is to achieve a state of the art drag level. In order to achieve such an aggressive target, feedback from aerodynamics has to be included in the early stage of the design decision process. The aerodynamic performance evaluation and improvement is mostly based on CFD simulation in combination with some wind tunnel testing for verification of the simulation results. As a first step in this process, a fully detailed simulation model is built. The styling surface is combined with engine room and underbody detailed geometry from a similar size existing vehicle. From a detailed analysis of the flow field potential areas for improvement are identified and five design parameters for modifying overall shape features of the upper body are derived. In a second step, a response surface method involving design of experiments and adaptive sampling techniques are applied for characterizing the effects of the design changes.

Adhesively bonded joints have been applied in the automotive industry for the past few decades due to their advantages such as higher fatigue resistance, light weight, capability of joining dissimilar materials, good energy absorption, and high torsional stiffness for overall body structure. They also provide an effective seal against noise and vibration at a low cost. There exists the challenge of defining the fatigue characteristics of adhesive joints under cyclic loading conditions, and conventional methods have limitations in detecting the crack initiation of a bonded joint. This study introduces a method of detecting crack initiation by using the frequency method. It is found that stiffness change in the system is highly correlated to change in natural frequencies. By monitoring the change in natural frequencies, the crack initiation can be detected.

This paper reports on DaimlerChrysler's participation in the Ad Hoc Diesel Fuels Test Program. This program was initiated by the U.S. Department of Energy and included major U.S. auto makers, major U.S. oil companies, and the Department of Energy. The purpose of this program was to identify diesel fuels and fuel properties that could facilitate the successful use of compression ignition engines in passenger cars and light-duty trucks in the United States at Tier 2 and LEV II tailpipe emissions standards. This portion of the program focused on minimizing engine-out particulates and NOx by using selected fuels, (not a matrix of fuel properties,) in steady state dynamometer tests on a modern, direct injection, common rail diesel engine.

The heat generation rate of a lithium ion cell was estimated using a reversible heat generation rate equation. Because the equation is based on the energy conservation law, the influence of kinetically slow processes should be considered. In this analysis, the influence of kinetically slow processes is present but it is small within the domain of the test measurements. This approximation can be of significant usefulness for modeling the thermal response of single cells and multi-cell batteries.

With the increased market share of electric vehicles, the demand for energy-efficient routing algorithms specifically optimized for electric vehicles has increased. Traditional routing algorithms are focused on optimizing the shortest distance or the shortest time in finding a path from point A to point B. These traditional methods have been working well for fossil fueled vehicles. Electric vehicles, on the other hand, require different route optimization techniques. Negative edge costs, battery power limits, battery capacity limits, and vehicle parameters that are only available at query time, make the task of electric vehicle routing a challenging problem. In this paper, we present an ant colony based, energy-efficient routing algorithm that is optimized and designed for electric vehicles. Simulation results show improvements in the energy consumption of electric vehicles when applied to a start-to-destination routing problem.