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This paper contributes to the Committee on Commonized Aerodynamics Automotive Testing Standards (CAATS) initiative, established by the late Gary Elfstrom. It is collaboratively compiled by automotive wind tunnel users and operators within the Subsonic Aerodynamic Testing Association (SATA). Its specific focus lies in automotive wind tunnel test techniques, encompassing both those relevant to passenger car and race car development. It is part of the comprehensive CAATS series, which addresses not only test techniques but also wind tunnel calibration, uncertainty analysis, and wind tunnel correction methods. The core objective of this paper is to furnish comprehensive guidelines for wind tunnel testing and associated techniques. It begins by elucidating the initial wind tunnel setup and vehicle arrangement within it.

Controller area network (CAN), FlexRay and local interconnect network (LIN) digital protocols are commonly used for communication in modern vehicles. A modern vehicle contains up to 70 electronic control units. This paper is a literature review of these protocols. We have also implemented LIN protocol. The communication cycle, process, message structure, and hardware elements are discussed for all three protocols. Performance is measured in terms of reliability and latency. In addition, a comparison between the CAN, FlexRay and LIN protocols is made. Experimental results indicate that CAN protocol has advantages when it comes to real-time priority-based communication. However, if all the events have equal priority, then FlexRay works well. The LIN protocol is budget friendly and has lowest cost in all 3 protocols but at the same time it is unreliable.

Recently developed gasoline engines utilize more aggressive EGR rate to meet the emissions and fuel economy regulations. The EGR temperature is often estimated by the ECU and its accuracy affects the estimations of EGR flow rate and intake air flow rate and temperature. Therefore, the accuracy of EGR temperature estimation becomes more important than ever for precise EGR rate control. Typical lookup map based EGR cooler model without the sensitivity to the coolant flow rate is acceptable and widely used if the heat capacity of the coolant side is high enough. However, the coolant flow rate under real vehicle driving conditions often visit low-speed high-load part of the engine map where the lookup map based model suffers from the accuracy issues. This paper presents an investigation of the accuracy of the lookup map based model under different heat capacity conditions. In this study, a simple EGR cooler model based on effectiveness-NTU method was also developed.

Controller area network (CAN) is used as a legacy protocol for in-vehicle communication. However, it lacks basic security features such as message authentication, integrity, confidentiality, etc., because the sender information in the message is missing. Hence, it is prone to different attacks like spoofing attacks, denial of service attacks, man in the middle and masquerade attacks. Researchers have proposed various techniques to detect and prevent these attacks, which can be split into two classes: (a) MAC-based techniques and (b) intrusion detection-based techniques. Further, intrusion detection systems can be divided into four categories: (i) message parameter- based, (ii) entropy-based, (iii) machine Learning-based and (iv) fingerprinting-based. This paper details state-of- the-art survey of fingerprinting-based intrusion detection techniques. In addition, the advantages and limitations of different fingerprinting-based intrusion detection techniques methods will be discussed.

Adverse weather conditions degrade the quality of images used in vision-based advanced driver assistance systems (ADAS) and autonomous driving algorithms. Adherent raindrops onto a vehicle’s windshield occlude parts of the input image and blur background texture in regions covered by them. Rain also changes image intensity and disturbs chromatic properties of color images. In this work, we collected a dataset using a camera mounted behind a windshield at different rain intensities. The data was processed to generate a set of distorted images by adherent raindrops along with ground truth data of clear images (just after a windshield wipe). We quantitatively evaluated the amount of distortion caused by the raindrops, using the Normalized Cross-Correlation and Structural Similarity methods.

Worldwide projections anticipate a fast-growing market share of the battery electric vehicles (BEVs) to meet stringent emissions regulations for global warming and climate change. One of the new challenges of BEVs is the effective and efficient thermal management of the BEV to minimize parasitic power consumption and to maximize driving range. Typically, the total efficiency of BEVs depends on the performance and power consumption of the thermal management system, which is highly affected by several factors, including driving environments (ambient temperature and traffic conditions) and driver's behavior (aggressiveness). Therefore, this paper investigates the influence of these factors on energy consumption by using a comprehensive BEV simulation integrated with a thermal management system model. The vehicle model was validated with experimental data, and a simulation study is performed by using the vehicle model over various traffic scenarios generated from a traffic simulator.

Cameras and image processing hardware are rapidly evolving technologies, which enable real-time applications for passenger cars, ground robots, and aerial vehicles. Visual odometry (VO) algorithms estimate vehicle position and orientation changes from the moving camera images. For ground vehicles, such as cars, indoor robots, and planetary rovers, VO can augment movement estimation from rotary wheel encoders. Feature-based VO relies on detecting feature points, such as corners or edges, in image frames as the vehicle moves. These points are tracked over frames and, as a group, estimate motion. Not all detected points are tracked since not all are found in the next frame. Even tracked features may not be correct since a feature point may map to an incorrect nearby feature point. This can depend on the driving scenario, which can include driving at high speed or in the rain or snow.

Global surrogate modeling aims to build surrogate model with high accuracy in the whole design domain. A major challenge to achieve this objective is how to reduce the number of function evaluations to the original computer simulation model. To date, the most widely used approach for global surrogate modeling is the adaptive surrogate modeling method. It starts with an initial surrogate model, which is then refined adaptively using the mean square error (MSE) or maximizing the minimum distance criteria. It is observed that current methods may not be able to effectively construct a global surrogate model when the underlying black box function is highly nonlinear in only certain regions. A new surrogate modeling method which can allocate more training points in regions with high nonlinearity is needed to overcome this challenge. This article proposes an efficient global surrogate modeling method based on a multi-layer sampling scheme.

Simulation based design and control optimization is widely used to assist the development of highly complex modern downsized turbocharged gasoline direct injection (GDI) engines. In such engines, knock phenomenon is a major constraint that limits performance and fuel economy enhancements. Thus, an accurate knock prediction model is critically important for virtual engine development process. In this paper, an enhanced ignition delay model is proposed for spark ignition (S)I combustion model based on previously developed empirical two-stage ignition delay model using fuel blends [1]. The ignition delay model provides a capability of predicting ignition delay of the end-gas zone for different fuel blends without additional calibration when fuel blending ratio changes. To adapt the ignition delay model to the SI combustion environment, the model is modified to have the sensitivity to the dilution effect by residual gas.

The potential for Augmented Reality (AR) spans many domains. Among other applications, AR can improve the discovery and learning experience for users inspecting a particular item. This paper discusses the use of AR in the automotive context; particularly, on improving the user experience in a dealership show room. Visual augmentation, through a tablet computer or glasses allows users to take part in a self-guided tour in learning about the various features, details, and options associated with a vehicle. The same approach can be applied to other learning scenarios, such as training and maintenance assistance. We evaluated a set of AR Glasses and a general purpose tablet. A table-top showroom was developed demonstrating what the actual user experience would be like for a self-guided dealership tour using natural markers and three-dimensional content spatially registered to physical objects in the user’s field of view.

To reliably implement driver-assist features and ultimately self-driving cars, autonomous driving systems will likely rely on a variety of sensor types including GPS, RADAR, LASER range finders, and cameras. Cameras are an essential sensory component because they lend themselves to the task of identifying object types that a self-driving vehicle is likely to encounter such as pedestrians, cyclists, animals, other cars, or objects on the road. In this paper, we present a feature-based visual odometry algorithm based on a stereo-camera to perform localization relative to the surrounding environment for purposes of navigation and hazard avoidance. Using a stereo-camera enhances the accuracy with respect to monocular visual odometry. The algorithm relies on tracking a local map consisting of sparse 3D map points. By tracking this map across frames, the algorithm makes use of the full history of detected features which reduces the drift in the estimated motion trajectory.

Injury Risk Curves are developed from cadaver data for sternal deflections produced by anterior, distributed chest loads for a 25, 45, 55, 65 and 75 year-old Small Female, Mid-Size Male and Large Male based on the variations of bone strengths with age. These curves show that the risk of AIS ≥ 3 thoracic injury increases with the age of the person. This observation is consistent with NASS data of frontal accidents which shows that older unbelted drivers have a higher risk of AIS ≥ 3 chest injury than younger drivers.

Injury risk curves for SID-IIs thorax and abdomen rib deflections proposed for future NCAP side impact evaluations were developed from tests conducted with the SID-IIs FRG. Since the floating rib guide is known to reduce the magnitude of the peak rib deflections, injury risk curves developed from SID-IIs FRG data are not appropriate for use with SID-IIs build level D. PMHS injury data from three series of sled tests and one series of whole-body drop tests are paired with thoracic rib deflections from equivalent tests with SID-IIs build level D. Where possible, the rib deflections of SID-IIs build level D were scaled to adjust for differences in impact velocity between the PMHS and SID-IIs tests. Injury risk curves developed by the Mertz-Weber modified median rank method are presented and compared to risk curves developed by other parametric and non-parametric methods.

In 1983, General Motors Corporation (GM) petitioned the National Highway Traffic Safety Administration (NHTSA) to allow the use of the biofidelic Hybrid III midsize adult male dummy as an alternate test device for FMVSS 208 compliance testing of frontal impact, passive restraint systems. To support their petition, GM made public to the international automotive community the limit values that they imposed on the Hybrid III measurements, which were called Injury Assessment Reference Values (IARVs). During the past 20 years, these IARVs have been updated based on relevant biomechanical studies that have been published and scaled to provide IARVs for the Hybrid III and CRABI families of frontal impact dummies. Limit values have also been developed for the biofidelic side impact dummies, BioSID, ES-2 and SID-IIs.

Brake pad to rotor adhesion following exposure to corrosive environments, commonly referred to as “stiction”, continues to present braking engineers with challenges in predicting issues in early phases of development and in resolution once the condition has been identified. The goal of this study took on two parts - first to explore trends in field stiction data and how testing methods can be adapted to better replicate the vehicle issue at the component level, and second to explore the impacts of various brake pad physical properties variation on stiction propensity via a controlled design of experiments. Part one will involve comparison of various production hardware configurations on component level stiction tests with different levels of prior braking experience to evaluate conditioning effects on stiction breakaway force.

For higher mileage vehicles, noise from contaminant ingress is one of the largest durability issues for wheel bearings. The mileage that wheel bearing sealing issues increase can vary due to multiple factors, such as the level of corrosion for the vehicle and the mating components around the wheel bearing. In general, sealing issues increase after 20,000 to 30,000 km. Protecting the seals from splash is a key step in extending bearing life. Benchmarking has shown a variety of different brake corner designs to protect the bearing from splash. This report examines the effect of factors from different designs, such as the radial gap between constant velocity joint (CVJ) slinger and the knuckle, knuckle labyrinth height and varying slinger designs to minimize the amount of splash to the bearing inboard seal. This report reviews some of the bearing seal failure modes caused by splash.

The strong focus on reducing brake drag, driven by a historic ramp-up in global fuel economy and carbon emissions standards, has led to renewed research on brake caliper drag behaviors and how to measure them. However, with the increased knowledge of the range of drag behaviors that a caliper can exhibit comes a particularly vexing problem - how should this complex range of behaviors be represented in the overall road load of the vehicle? What conditions are encountered during coastdown and fuel economy testing, and how should brake drag be measured and represented in these conditions? With the Environmental Protection Agency (amongst other regulating agencies around the world) conducting audit testing, and the requirement that published road load values be repeatable within a specified range during these audits, the importance of answering these questions accurately is elevated. This paper studies these questions, and even offers methodology for addressing them.

Connectivity has become an essential need for daily device users. With the car projected to be the “ultimate mobile device”, connectivity modules will eventually be mainstream in every car. Network providers are expanding their infrastructure and technology to accommodate the connected cars. Besides making voice and emergency calls the connected car will be sharing data with telematics service providers, back end systems and other vehicles. This trend will increase vehicle modules, complexity, entry points and vulnerabilities. This paper will present the current connected car architectures. The paper will present current architectural issues of the connected car and its vulnerabilities. The paper will present a new proposed architecture for the future connected car that enhances efficiency and security.

Today open source software is widely used in different domains like Desktop systems, Consumer electronics (smart phones, TV, washing machines, camera, printers, smart watches), Automotive, Automation etc. With the increased involvement of the open source software in the different domains including the safety critical ones, there has been a requirement of the well-defined test strategy to test and verify such systems. Currently there are multiple open source tools and frameworks to choose from. The paper describes the various open source test strategies and tools available to qualify such systems, their features, maintenance, community support, advantages and disadvantages. Target audience would be the software engineers, program managers, using an open source stack for the product development.

The human thermal comfort, which has been a subject of extensive research, is a principal objective of the automotive climate control system. Applying the results of research studies to the practical problems require quantitative information of the thermal environment in the passenger compartment of a vehicle. The exposure to solar radiation is known to alter the thermal environment in the passenger compartment. A photovoltaic-cell based sensor is commonly used in the automotive climate control system to measure the solar radiation exposure of the passenger compartment of a vehicle. The erroneous information from a sensor however can cause thermal discomfort to the occupants. The erroneous measurement can be due to physical or environmental parameters. Shading of a solar sensor due to the opaque vehicle body elements is one such environmental parameter that is known to give incorrect measurement.