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The AutoDrive Challenge competition sponsored by General Motors and SAE gives undergraduate and graduate students an opportunity to get hands-on experience with autonomous vehicle technology and development as they work towards their degree. Michigan Technological University has participated in the AutoDrive Challenge since its inception in 2017 with students participating through MTU’s Robotic System Enterprise. The MathWorks Simulation Challenge has been a component of the competition since its second year, tasking students with the development of perception, control and testing algorithms using MathWorks software products. This paper presents the pedagogical approach graduate student mentors used to enable students to build their understanding of autonomous vehicle concepts using familiar tools. This approach gives undergraduate students a productive experience with these systems that they may not have encountered in coursework within their academic program.

The study of spray-wall interaction is of great importance to understand the dynamics during fuel-surface impingement process in modern internal combustion engines. The identification of droplet post-impingement pattern (contact, transition, non-contact) and droplet characteristics can quantitatively provide an estimation of energy transfer for spray-wall interaction, thus further influencing air-fuel mixing and emissions under combusting conditions. Theoretical criteria of single droplet post-impingement pattern on a dry wall have been experimentally and numerically studied by many researchers to quantify the hydrodynamic droplet behaviors. However, apart from model fidelity, another issue is the scalability. A theoretical criterion developed from one case might not be well suited to another scenario. In this paper, a data-driven approach for single droplet-dry wall post-impingement pattern utilizing arithmetical machine learning classification methods is proposed and demonstrated.

Off road navigation demands ground robots to traverse complex and often changing terrain. Classification and assessment of terrain can improve path planning strategies by reducing travel time and energy consumption. In this paper we introduce a terrain classification and assessment framework that relies on both exteroceptive and proprioceptive sensor modalities. The robot captures an image of the terrain it is about to traverse and records corresponding vibration data during traversal. These images are manually labelled and used to train a support vector machine (SVM) in an offline training phase. Images have been captured under different lighting conditions and across multiple locations to achieve diversity and robustness to the model. Acceleration data is used to calculate statistical features that capture the roughness of the terrain whereas angular velocities are used to calculate roll and pitch angles experienced by the robot.

Battery temperature variations have a strong effect on both battery aging and battery performance. Significant temperature variations will lead to different battery behaviors. This influences the performance of the Hybrid Electric Vehicle (HEV) energy management strategies. This paper investigates how variations in battery temperature will affect Lithium-ion battery aging and fuel economy of a HEV. The investigated energy management strategy used in this paper is the Equivalent Consumption Minimization Strategy (ECMS) which is a well-known energy management strategy for HEVs. The studied vehicle is a Honda Civic Hybrid and the studied battery, a BLS LiFePO4 3.2Volts 100Ah Electric Vehicle battery cell. Vehicle simulations were done with a validated vehicle model using multiple combinations of highway and city drive cycles. The battery temperature variation is studied with regards to outside air temperature.

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.

Battery State of Charge (SOC) constraints are used to prevent the battery in Hybrid Electric Vehicles (HEVs) from over-charging or over-discharging. These constraints strongly influence the power-split of the HEV. This paper presents results on how Battery State of Charge (SOC) constraints effects Lithium ion battery aging and fuel economy when using the Equivalent Consumption Minimization Strategy (ECMS). The vehicle studied is the Honda Civic Hybrid. The battery used is A123 Systems’ ANR26650 battery cell. Vehicle simulation uses multiple combinations of highway and city drive cycles. For each combination of drive cycles, nine SOC constraints ranges are used. Battery aging is evaluated using a semi-empirical model combined with the accumulated Ah-throughput method which uses, as an input, the battery SOC trajectory from the vehicle simulations. The simulation results provide insight into how SOC constraints effect fuel economy as well as battery aging.

In this paper, we present a project being conducted at Yalong Educational Equipment Company on control of educational robots using discrete event system theory. An educational robot is a programmable robot to be used by students for training and learning. To model a robot, we divide the robot into nine physical modules. Each module is modeled as an automaton. Parallel composition is used to obtain the entire model. The robot can be programmed to perform sequences of basic tasks. We investigate six basic tasks and use supervisors to control and achieve the tasks. Desired languages are obtained for all tasks and supervisory control theory is used to synthesize supervisors. To reduce computational complexity, modular/coordinated supervisors are used

This paper details the development of a test-bench simulation to characterize the behavior of an electro-hydraulic actuated dry clutch used in a pre-transmission parallel hybrid powertrain architecture of Wayne State University EcoCAR 3. Engage and disengage systems play a crucial role in a pre-transmission parallel hybrid architecture. The most common device used to meet the purpose of physically connecting internal combustion engine and electric powertrains is a dry clutch. Its own characteristics and capabilities allow its usage for this application. The transition between the pure electric and hybrid modes is dictated by the main control strategy. Therefore, the engaging system will be widely used when switching from charge depleting to charge sustaining mode, and vice versa. In addition, when torque is required from both sources for higher performance, the clutch will be responsible for mechanically connecting both torque sources.

Contemporary manufacturing systems are still evolving. The system elements, layouts, and integration methods are changing continuously, and ‘collaborative robots’ (CoBots) are now being considered as practical industrial solutions. CoBots, unlike traditional CoBots, are safe and flexible enough to work with humans. Although CoBots have the potential to become standard in production systems, there is no strong foundation for systems design and development. The focus of this research is to provide a foundation and four tier framework to facilitate the design, development and integration of CoBots. The framework consists of the system level, work-cell level, machine level, and worker level. Sixty-five percent of traditional robots are installed in the automobile industry and it takes 200 hours to program (and reprogram) them.

At the collision moment, a driver’s lower extremity will be in different foot position, which leads to the different posture of the lower extremity with various muscle activations. These will affect the driver’s injury during collision, so it is necessary to investigate further. A simulated collision scene was constructed, and 20 participants (10 male and 10 female) were recruited for the test in a driving simulator. The braking posture and muscle activation of eight major muscles of driver’s lower extremity (both legs) were measured. The muscle activations in different postures were then analyzed. At the collision moment, the right leg was possible to be on the brake (male, 40%; female, 45%), in the air (male, 27.5%; female, 37.5%) or even on the accelerator (male, 25%; female, 12.5%). The left leg was on the floor all along.

Many metrics have been used in an attempt to predict the effects of secondary tasks on driving behavior. Such metrics often give rise to seemingly paradoxical results, with one metric suggesting increased demand and another metric suggesting decreased demand for the same task. For example, for some tasks, drivers maintain their lane well yet detect events relatively poorly. For other tasks, drivers maintain their lane relatively poorly yet detect events relatively well. These seeming paradoxes are not time-accuracy trade-offs or experimental artifacts, because for other tasks, drivers do both well. The paradoxes are resolved if driver demand is modeled in two orthogonal dimensions rather than a single “driver workload” dimension. Principal components analysis (PCA) was applied to the published data from four simulator, track, and open road studies of visual-manual secondary task effects on driving.

Panel Discussions held at the SAE World Congress in both 2013 and 2014 observed that a shortage of good quality engineering talent formed a chronic and major challenge. (“Good quality” refers to applicants that would be shortlisted for interview.) While doubts have been expressed in some quarters, the shortage is confirmed by automotive sector employers and the Panel's view was that it was symptomatic of a range of issues, all of which have some bearing on the future of the profession. Initiatives to improve recruitment and retention have had varying degrees of success. Efforts need to be intensified in primary schools where negative perceptions develop and deepen. Schemes like AWIM that operate on a large scale and are designed to supplement school curricula should operate at an international level. Universities represent the entry point into the engineering profession and their role in the recruitment process as well as education and training is crucial.

The Wayne State University EcoCAR2 team provided its members with Modeling and Simulation training course for the second summer of the competition. EcoCAR2 is a three-year Advanced Vehicle Technology Competition (AVTC) sponsored by General Motors and the Department of Energy. The course lasted three months and included 45 hours of formal lectures and class hands-on work and an estimated one hundred and fifty hours in home assignments that directly contributed to the team's deliverables. The course described here is unique. The design and class examples were extracted from an in-house complete vehicle simulation and control code to ensure hands-on, interactive training based on real-world problems. The course investigated the physics behind every major powertrain component of a hybrid electric vehicle and the different ways to model the components into a full vehicle simulation.

The paper describes an experimental activity on the spatial and temporal liquid- and vapor-phase distributions of diesel fuel at engine-like conditions. The influence of the k-factor (0 and 1.5) of a single-hole axial-disposed injector (0.100 mm diameter and 10 L/d ratio) has been studied by spraying fuel in an optically-accessible constant-volume combustion vessel. A high-speed imaging system, capable of acquiring Mie-scattering and Schlieren images in a near simultaneous fashion mode along the same line of sight, has been developed at the Michigan Technological University using a high-speed camera and a pulsed-wave LED system. The time resolved pair of schlieren and Mie-scattering images identifies the instantaneous position of both the vapor and liquid phases of the fuel spray, respectively. The studies have been performed at three injection pressures (70, 120 and 180 MPa), 23.9 kg/m3 ambient gas density and 900 K gas temperature in the vessel.

The Wayne State University (WSU) EcoCAR2 student team designed, modeled, Model-In-the-Loop (MIL) tested, Software-In-the-Loop (SIL) simulation tested, and Hardware-In-the-Loop (HIL) simulation tested the team's conversion design for taking a 2013 Chevrolet Malibu and converting it into a Parallel-Through-The-Road (PTTR) plug-in hybrid. The 2013 Malibu is a conventional Front Wheel Drive (FWD) vehicle and the team's conversion design keeps the conventional FWD and adds a Rear Wheel Drive (RWD) powertrain consisting of an electric motor, a single speed reduction gearbox and a differential to drive the rear wheels -where none of these previously existed on the rear wheels. The RWD addition creates the PTTR hybrid powertrain architecture of two driven axles where the mechanical torque path connection between the two powertrains is through the road, rather than a mechanical torque path through gears, chains, or shafts.

The Wayne State University (WSU) EcoCAR2 student team is participating in a design competition for the conversion of a 2013 Chevrolet Malibu into a plug-in hybrid. The team created a repeatable on-road test drive route using local public roads near the university that would be of similar velocity ranges contained in the EcoCAR2 4-Cycle Drive Schedule - a weighted combination of four different EPA-based drive cycles (US06 split into city and highway portions, all of the HWFET, first 505 seconds portion of UDDS). The primary purpose of the team's local on-road route was to be suitable for testing the team's added hybrid components and control strategy for minimizing petroleum consumption and tail pipe emissions. Comparison analysis of velocities was performed between seven local routes and the EcoCAR2 4-Cycle Drive Schedule. Three of the seven local routes had acceptable equivalence for velocity (R₂ ≻ 0.80) and the team selected one of them to be the on-road test drive route.

Up to now, there is no standard methodology that addresses how driver distraction is affected by perceptual demand and working memory demand - aside from visual allocation. In 2009, the Peripheral Detection Task (PDT) became a NHTSA recommended measure for driver distraction [1]. Then the PDT task was renamed as the Detection Response Task (DRT) because the International Standards Organization (ISO) has identified this task as a potential method for assessing selective attention in detection of visual, auditory, tactile and haptic events while driving. The DRT is also under consideration for adoption as an ISO standard surrogate test for driver performance for new telematics designs. The Wayne State University (WSU) driver imaging group [2, 3] improved the PDT and created the Enhanced Peripheral Detection Task I (EPDT-I) [4]. The EPDT-I is composed of a simple visual event detection task and a video of a real-world driving scene.

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.

In this paper, we proposed a distributed Engineering Computer Aided Learning System. Instead of attending engineering teaching sessions, engineering students are able to interact with the software to gain the same amount of teaching materials. Besides, they will interact with other engineering students from other Engineering schools. The proposed software has the ability to examine the student step by step to reach certain goals. The training and the examination will be different based on the student level and his learning process. Using this system the role of excellent professor can be achieved. The software will have two sessions, i.e. test session and learning session. The software provides the capability of knowledge sharing between multi schools and different educational systems that can provide the students with a large set of training materials. The system was built using JAVA programming language.

Speed and accuracy are the critical needs in software for the modeling and simulation of vehicle cooling systems. Currently, there are two approaches used in commercially available thermal analysis software packages: 1) detailed modeling using complex and sophisticated three-dimensional (3D) heat transfer and computational fluid dynamics, and 2) rough modeling using one-dimensional (1D) simplistic network solvers (flow and thermal) for quick prediction of flow and thermal fields. The first approach offers accuracy at the cost of speed, while the second approach provides the simulation speed, sacrificing accuracy and can possibly lead to oversimplification. Therefore, the analyst is often forced to make a choice between the two approaches, or find a way to link or couple the two methods. The linking between one-dimensional and three-dimensional models using separate software packages has been attempted and successfully accomplished for a number of years.