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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 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.

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.

This paper presents an experimental study of the cycle-averaged, local surface heat transfer, from the exhaust gases to a straight pipe extension of the exhaust port of a four-cylinder spark-ignition (SI) engine, over a wide range of engine operating conditions, from 1000 rpm, light load, through 4000 rpm, full load. The local steady-state heat flux was well correlated by a Nusselt-Reynolds number relationship that included entrance effects. These effects were found to be the major contributor to the local heat transfer augmentation. The Convective Augmentation Factor (CAF), which is defined as the ratio of the measured heat flux to the corresponding heat flux for fully-developed turbulent pipe flow, was found to decrease with increasing Reynolds number and increasing axial distance from the entrance of the test section.

The number of EVs are increasing in power distribution systems every day. This research analyses different penetration levels of electric vehicles in power distribution systems to provide stable energy for smart devices and observes its impacts on operational costs and environmental emissions. The supply of EV power is determined based on smart device consumption by optimal energy management of EV batteries so that both the utilities and the car owner get benefits. Utilities can save energy by reducing system loss, while EV owners can earn money by selling it to utilities at their convenient time for smart device operations. The PG&E 69-bus distribution system is used for the simulation and case studies. Case studies in this research show how the power management of EV's batteries charging and discharging characteristics benefits both utilities and EV owners. The uncertainty of the driving pattern of EVs is also considered in the research to get more accurate results.

This paper presents nonlinear system identification of a variable oil pump for model-based controls and diagnostics of advanced internal combustion engines. The variable oil pump offers great benefits over the conventional fixed displacement oil pump in terms of fuel efficiency and functional optimality. However, to fully benefit from the variable oil pump, an accurate mathematical model that describes its dynamic behavior is foundational to develop an accurate and robust oil pressure control and diagnostic. Toward this end, Hammerstein and Wiener models that consist of a nonlinear static block followed by a linear dynamic block and a linear dynamic block followed by a nonlinear static block, respectively are developed. Under different operating conditions (oil temperature and engine speed), the oil pressure (output) is measured with the multilevel duty cycle (input) of the flow control valve.

A significant amount of residual stresses can be developed in aluminum castings during heat treatment. This paper reports an experimental study of the residual stress distributions in aluminum castings after solution treatment and water quench. The residual stresses in aluminum castings are measured using both optical and resistance strain rosettes. The optical strain rosette technique was recently developed in conjunction with ring-core cutting method for residual stress measurement. The measured residual stresses from optical and resistance strain rosettes are compared with the results of X-ray and neutron diffraction measurements. The advantages and disadvantages of various measurement methods are discussed.

Scuffing is a failure mechanism which can occur in various engineering components, such as engine cylinder kits, gears and cam/followers. In this research, the scuffing behavior of 4140 steel and ductile iron was investigated and compared through ball-on-disk scuffing tests. A step load of 22.2 N every two minutes was applied with a light mineral oil as lubricant to determine the scuffing load. Both materials were heat treated to various hardness and tests were conducted to compare the scuffing behavior of the materials when the tempered hardness of each material was the same. Ductile iron was found to have a consistently high scuffing resistance before tempering and at tempering temperatures lower than 427°C (HRC ≻45). Above 427°C the scuffing resistance decreases. 4140 steel was found to have low scuffing resistance at low tempering temperatures, but as the tempering temperature increases, the scuffing resistance increased.

This research studies the transformation kinetics of austempered ductile iron (ADI) with and without nickel as the main alloying element. ADI has improved mechanical properties compared to ductile iron due to its ausferrite microstructure. Not only can austempered ductile iron be produced with high strength, high toughness and high wear resistance, the ductility of ADI can also be increased due to high carbon content austenite. Many factors influence the transformation of phases in ADI. In the present work, the addition of nickel was investigated based on transformation kinetics and metallography observation. The transformation fractions were determined by Rockwell hardness variations of ADI specimens. The calculation of transformation kinetics and activation energy using the “Avrami Equation” and “Arrhenius Equation” is done to describe effects of nickel alloy for phase reactions.

The residual stresses found in components are mainly due to thermal, mechanical and metallurgical changes of material. The manufacturing processes such as fabrication, assembly, welding, rolling, heat treatment, shot peening etc. generate residual stresses in material. The influence of residual stress can be beneficial or detrimental depending on nature and distribution of the residual stress in material. In general, the compressive residual stress can increase the fatigue life of material because it provides greater resistance for crack initiation and propagation. A significant number of improvements for residual stress measurement techniques have occurred in last few decades. The most popular technique of residual stress measurement is based on the principle of strain gage rosette and hole drilling (ASTM E837-01, destructive).

Nitridng usually improves wear resistance and can be accomplished using a gas or plasma method; it's necessary to find if there is any difference in surface roughness, wear and/or wear mechanism when choosing between methods for nitriding. In this study, Ball-on-disk wear test was compared on coupons nitrided with five different nitriding cycles that processed at temperatures of 500-570°C, with a processing time of 8 - 80 hrs. Different compound layer thicknesses were formed, (5-8μm), and a minimum of 0.38 mm case depth was produced. Nitrided samples were also compared to nitrocarburized and the nitrided coupons with a “0” compound layer in a ball-on-disk test. Few selected coupons were post-polished and wear test on ball-on-disk test was compared with the coupons without post polishing. Optical surface roughness using White Light Interferometry (WLIM) and metallurgical testing was performed.