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Over the past decade there has been significant development in Automated Driving (AD) with continuous evolution towards higher levels of automation. Higher levels of autonomy increase the vehicle Dynamic Driving Task (DDT) responsibility under certain predefined Operational Design Domains (in SAE level 3, 4) to unlimited ODD (in SAE level 5). The AD system should not only be sophisticated enough to be operable at any given condition but also be reliable and safe. Hence, there is a need for Automated Vehicles (AV) to undergo extensive open road testing to traverse a wide variety of roadway features and challenging real-world scenarios. There is a serious need for accurate Ground Truth (GT) to locate the various roadway features which helps in evaluating the perception performance of the AV at any given condition. The results from open road testing provide a feedback loop to achieve a mature AD system.

Today’s advanced vehicles have high degree of interaction due to numerous sensors, actuators and also with complex communication within the control units. In order to hack a vehicle, it has to be within a certain range of communication. Here, we discuss the On-Board Diagnostic (OBD) regulations for next generation BEV/HEV, its vulnerabilities and cybersecurity threats that come with hacking. We propose three cybersecurity attack detection and defense methods: Cyber-Attack detection algorithm, Time-Based CAN Intrusion Detection Method and, Feistel Cipher Block Method. These control methods autonomously diagnose a cybersecurity problem in a vehicle’s onboard system using an OBD interface, such as OBD-II when a fault caused by a cyberattack is detected, All of this is achieved in an internal communication network structure. The results discussed here focus on the first detection method that is Cyber-Attack detection algorithm.

This paper presents experimental investigations of determining and analyzing low-frequency, low-SNR (Signal to Noise Ratio) noise sources of an automobile by using a new technology known as Sound Viewer. Such a task is typically very difficult to do especially at low or even negative SNR. The underlying principles behind the Sound Viewer technology consists of a passive SODAR (Sonic Detection And Ranging) and HELS (Helmholtz Equation Least Squares) method. The former enables one to determine the precise locations of multiple sound sources in 3D space simultaneously over the entire frequency range consistent with a measurement microphone in non-ideal environment, where there are random background noise and unknown interfering signals. The latter enables one to reconstruct all acoustic quantities such as the acoustic pressure, acoustic intensity, time-averaged acoustic power, radiation patterns, etc.

Use of ethanol as gasoline replacement can contribute to the reduction of nitrogen oxide (NOx) and carbon oxide (CO) emissions. Depending on ethanol production, significant reduction of greenhouse-gas emissions is possible. Concentration of certain species, such as unburned ethanol and acetaldehyde in the engine-out emissions are known to rise when ratio of ethanol to gasoline increases in the fuel. This research explores on hydrous ethanol fueled port-fuel injection (PFI) spark ignition (SI) engine emissions that contribute to photochemical formation of ozone, or so-called ozone precursors and the precursor of peroxyacetyl nitrates (PANs). The results are compared to engine operation on gasoline. Concentration obtained by FTIR gas analyzer, and mass-specific emissions of formaldehyde (HCHO), acetaldehyde (MeCHO) and methane (CH4) under two engine speed, four load and two spark advance settings are analyzed and presented.

The Hotelling multivariate control chart and the sample generalized variance |S| are used to monitor the mean and dispersion of vehicle build vision data including the pallet information to identify the non-conforming pallets that are used in body shops of FCA US LLC assembly plants. An iterative procedure and the Gaussian mixture model (GMM) are used to rank the non-conforming or bad pallets in the order of severity. The Hotelling multivariate T2 test statistic along with Mason-Tracy-Young (MYT) signal decomposition method is used to identify the features that are affected by the bad pallets. These algorithms were implemented in the Advanced Pallet Analysis module of the FCA US software Body Shop Analysis Toolbox (BSAT). The identified bad pallets are visualized in a scatter plot with a different color for each of the top bad pallets. The run chart of an affected feature confirms the bad pallet by highlighting data points from the bad pallet.

This paper details the vehicle testing activities performed during the Year 4 of the EcoCAR 3 competition by the Wayne State University team on a Pre-Transmission Parallel PHEV. The paper focuses on two main testing platforms: the chassis dynamometer and the closed-course track (on-road). The focus of the former is to evaluate the emissions and energy consumption associated with different driving scenarios, while the latter has been used to assess the vehicle performance and their impact on the consumer appeal. The paper presents the objectives of each test, the setup accomplished for the different vehicle testing platforms, the results obtained and the comparison with the values expected from simulations. In addition, the impact of the results on the refinement of the control strategies and on the validation of the simulation models are discussed.

This paper details the Wayne State University development of the Hybrid Supervisory Controller strategies for the Year 3 of the EcoCAR 3 competition. Included in this paper are the processes for developing the strategies for the supervisory control system, which includes the torque distribution among the powertrain components, and the diagnostic strategies adopted to guarantee the safety critical functionalities of the vehicle. The EcoCAR 3 competition challenges sixteen North American universities to re-engineer the 2016 Chevrolet Camaro to reduce its environmental impact without compromising its performance and consumer acceptability. During the Year 3 of the competition the team has refined the control strategies designed in the previous years, to enable the powertrain full functionalities and achieve better energy consumption over pre-determined drive cycles.

Reactivity Controlled Compression Ignition (RCCI) is an approach to increase engine efficiency and lower engine-out emissions by using in-cylinder stratification of fuels with differing reactivity (i.e., autoignition characteristics) to control combustion phasing. Stratification can be altered by varying the injection timing of the high-reactivity fuel, causing transitions across multiple regimes of combustion. When injection is sufficiently early, combustion approaches a highly-premixed autoignition regime, and when it is sufficiently late it approaches more mixing-controlled, diesel-like conditions. Engine performance, emissions, and control authority over combustion phasing with injection timing are most favorable in between, within the RCCI regime.

The superior fuel economy of direct injection internal combustion engines (diesel and gasoline) is related to use of a high compression ratio to auto-ignite the fuel and the overall lean combustible mixture. Two of the major problems in diesel engine emissions are the NOx and soot emissions, which are caused by the heterogeneity of the charge and the properties of the diesel fuel. Conventional Direct Injection Spark Ignition Gasoline engines don't have these problems because of the fuel properties particularly its volatility. However, its efficiency and specific power output are limited by the knock, knock produced preignition and the sporadic preignition phenomenon. The Gasoline Direct Injection Compression Ignition (GDICI) engine combines the superior features of the two engines by increasing the compression ratio and use of gasoline as a fuel.

With increasing interest to reduce the dependency on gasoline and diesel, alternative energy source like compressed natural gas (CNG) is a viable option for internal combustion engines. Spark-ignited (SI) CNG engine is the simplest way to utilize CNG in engines, but direct injection (DI) Diesel-CNG dual-fuel engine is known to offer improvement in combustion efficiency and reduction in exhaust gases. Dual-fuel engine has characteristics similar to both SI engine and diesel engine which makes the combustion process more complex. This paper reports the computational fluid dynamics simulation of both DI dual-fuel compression ignition (CI) and SI CNG engines. In diesel-CNG dual-fuel engine simulations and comparison to experiments, attention was on ignition delay, transition from auto-ignition to flame propagation and heat released from the combustion of diesel and gaseous fuel, as well as relevant pollutants emissions.

The present work is concerned with the objective of developing a process for practical multi-disciplinary design optimization (MDO). The main goal adopted here is to minimize the weight of a vehicle body structure meeting NVH (Noise, Vibration and Harshness), durability, and crash safety targets. Initially, for simplicity a square tube is taken for the study. The design variables considered in the study are width, thickness and yield strength of the tube. Using the Response Surface Method (RSM) and the Design Of Experiments (DOE) technique, second order polynomial response surfaces are generated for prediction of the structural performance parameters such as lowest modal frequency, fatigue life, and peak deceleration value. The optimum solution is then obtained by using traditional gradient-based search algorithm functionality “fmincon” in commercial Matlab package.

Inverse kinematic solutions of six degree of freedom (DOF) robot manipulation is a challenging task due to complex kinematic structure and application conditions which affects and depend on the robot’s tool frame position, orientation and different possible configurations. The robot trajectory represents a series of connected points in three dimensional space. Each point is defined with its position and orientation related to the robot’s base frames or users teach pendant. The robot will move from point to point using the desired motion type (linear, arc, or joint). This motion requires inverse kinematic solution. This paper presents a detailed inverse kinematic solution for Fanuc 6R (Rotational) robot family using a geometrical method. Each joint angular position will be geometrically analyzed and all possible solutions will be included in the decision equations. The solution will be developed in a parametric manner to cover the complete Fanuc six DOF family.

The present work is concerned with the objective of multi disciplinary design optimization (MDO) of an automotive front end structure using truncated finite element model. A truncated finite element model of a real world vehicle is developed and its efficacy for use in design optimization is demonstrated. The main goal adopted here is minimizing the weight of the front end structure meeting NVH, durability and crash safety targets. Using the Response Surface Method (RSM) and the Design Of Experiments (DOE) technique, second order polynomial response surfaces are generated for prediction of the structural performance parameters such as lowest modal frequency, fatigue life, and peak deceleration value.

Gasoline-direct-injection (GDI) engines have been adopted increasingly by the automotive industry in the recent years due to their performance, effects on the environment, and customers' demand on advanced technology. However, the knowledge of detailed combustion process in such engines is still not thoroughly analyzed and understood. With optically accessible engines (OAE) and advanced measuring techniques, such as high-speed digital imaging, the in-cylinder combustion process is made available directly to researchers. The present study primarily focuses on the effects of different parameters of engine control on the combustion process, such as fuel types, valve deactivation, ignition timing, spark energy, injection timing, air-fuel ratio, and exhaust gas recirculation. Three engine heads of a 2.0L GDI engine are used with modification to acquire different optical access.

The Wayne State University (WSU) EcoCAR 2 Team designed the conversion of a GM donated 2013 Chevrolet Malibu to a Parallel-Through-The-Road (PTTR) Plug-In Hybrid vehicle within a 9 month timeframe. This fast prototyping project used the EcoCAR 2 Vehicle Development Process (EVDP). Various tradeoffs were made to meet all competition requirements and to make the vehicle as competitive as possible within budget, time and experience limitations. The chosen PTTR architecture, nicknamed by the team as “E2D2” (Ethanol-Electric Dual-Drivetrain), provides up to 35.7 electric only miles and a fuel economy of 60 miles per gallons gasoline equivalent (mpgge) or 3.96 liters gasoline equivalent (lge) per one hundred km. This is accomplished using an E85 engine-driven front traction system and a battery-electric-motors-driven rear traction system. The team developed the control system and designed the packaging and integration of all required components including the Energy Storage System (ESS).

An iterative learning control (ILC) algorithm has been developed for a test cell electro-hydraulic, fully flexible valve actuation system to track valve lift profile under steady-state and transient operation. A dynamic model of the plant was obtained from experimental data to design and verify the ILC algorithm. The ILC is implemented in a prototype controller. The learned control input for two different lift profiles can be used for engine transient tests. Simulation and bench test are conducted to verify the effectiveness and robustness of this approach. The simple structure of the ILC in implementation and low cost in computation are other crucial factors to recommend the ILC. It does not totally depend on the system model during the design procedure. Therefore, it has relatively higher robustness to perturbation and modeling errors than other control methods for repetitive tasks.

The goal of optimization in vehicle design is often blurred by the myriads of requirements belonging to attributes that may not be quite related. If solutions are sought by optimizing attribute performance-related objectives separately starting with a common baseline design configuration as in a traditional design environment, it becomes an arduous task to integrate the potentially conflicting solutions into one satisfactory design. It may be thus more desirable to carry out a combined multi-disciplinary design optimization (MDO) with vehicle weight as an objective function and cross-functional attribute performance targets as constraints. For the particular case of vehicle body structure design, the initial design is likely to be arrived at taking into account styling, packaging and market-driven requirements.

As diesel emission regulations continue to increase, the use of exhaust aftertreatment systems containing, for example the diesel oxidation catalyst (DOC) and diesel particulate filter (DPF) will become necessary in order to meet these stringent emission requirements. The addition of a DOC and DPF in conjunction with utilizing biodiesel fuels requires extensive research to study the implications that biodiesel blends have on emissions as well as to examine the effect on aftertreatment devices. The proceeding work discusses results from a 2006 VM Motori four-cylinder 2.8L direct injection diesel engine coupled with a diesel oxidation catalyst and catalyzed diesel particulate filter. Tests were done using ultra low sulfur diesel fuel blended with 20% choice white grease biodiesel fuel to evaluate the effects of biodiesel emission products on the performance and effectiveness of the aftertreatment devices and the effect of low temperature combustion modes.

For the application of advanced clean combustion technologies, such as diesel HCCI/LTC, a compressor with high efficiency over a broad operation range is required to supply a high amount of EGR with minimum pumping loss. A compressor with high pitch of vaneless diffuser would substantially improve the flow range of the compressor, but it is at the cost of compressor efficiency, especially at low mass flow area where most of the city driving cycles resides. In present study, an ultra low solidity compressor vane diffuser was numerically investigated. It is well known that the flow leaving the impeller is highly distorted, unsteady and turbulent, especially at relative low mass flow rate and near the shroud side of the compressor. A conventional vaned diffuser with high stagger angle could help to improve the performance of the compressor at low end. However, adding diffuser vane to a compressor typically restricts the flow range at high end.

Nitro Fuel Funny cars have 7-8,000 hp and travel 330 mph in a quarter mile. These cars experience extreme forces in normal operation. One phenomenon familiar to drag racers is tire shake. Mild cases can cause loss of traction and vision. Extreme cases can cause injury or death. In March of 2007, a study and subsequent revision of the passenger compartment in a Fuel Funny car was performed after a fatal accident due to extreme tire shake. Tire shake on a drag race car normally occurs when the force on the rear tire causes the tire to roll over itself causing a loss of traction and side-to-side vibration. In other cases, if the tire fails at high speed, the tire may partially separate, causing an extreme vibration in the cockpit of the car. The vibration may set up a harmonic in the chassis, which is transferred to the driver since the rear end is bolted directly to the chassis with no suspension to absorb the energy.