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Technical Paper

Investigation in Bonding Conditions of CF/Epoxy – PP Hybrid Structures Manufactured by Hybrid Single Shot Method

2019-10-28
2019-01-2595
The hybrid single shot method is a novel manufacturing technique which allows to form and bond CF/Epoxy sheet with the injected thermoplastic in a single injection process. This process is promising to overcome the drawbacks of the traditional hybrid structure manufacturing methods by reducing the cycle time, energy consumption, tool, and machinery cost which are the concerns of automakers. In this process, polypropylene (PP) injected over the pre-heated CF/Epoxy prepreg insert. PP is widely used in automotive applications such as bumpers, dashboards, side-sills while CF/Epoxy prepreg has a great potential to enhance the mechanical properties of the hybrid component. Insert material is formed by the pressure of PP and bonded with the thermoplastic part by taking the advantages of polymer heat and the tackiness of prepreg. The final part is promising to combine the inherent properties of these two material while enhancing their weaknesses.
Technical Paper

Design of Experiments for Effects and Interactions During Brake Emissions Testing Using High-Fidelity Computational Fluid Dynamics

2019-09-15
2019-01-2139
The investigation and measurement of particle emissions from foundation brakes require the use of a special adaptation of inertia dynamometer test systems. To have proper measurements for particle mass and particle number, the sampling system needs to minimize transport losses and reduce residence times inside the brake enclosure. Existing models and spreadsheets estimate key transport losses (diffusion, turbophoretic, contractions, gravitational, bends, and sampling isokinetics). A significant limitation of such models is the inability to assess the complex turbulent flows and associated particle dynamics inside the brake enclosure, which is anticipated to be important. This paper presents a Design of Experiments (DOE) approach using Computational Fluid Dynamics (CFD) to predict the flow within a dynamometer enclosure under relevant operating conditions. The systematic approach allows the quantification of turbulence intensity, mean velocity profiles, and residence times.
Technical Paper

Quantification of Linear Approximation Error for Model Predictive Control of Spark Ignited Turbocharged Engines

2019-09-09
2019-24-0014
Modern turbocharged spark-ignition engines are being equipped with an increasing number of control actuators to simultaneously meet fuel economy, emissions and performance targets. The response time variations between a given set of engine control actuators tends to be significant during transients and necessitate highly complex actuator scheduling routines. Model Predictive Control (MPC) algorithms have the potential to significantly reduce calibration and control tuning efforts as compared to current methodologies that are designed around integration of multiple single-input single-output sub-system controllers. MPC systems simultaneously generate all actuator responses by using a combination of current engine conditions and optimization of a control-oriented plant model. To achieve real-time control the engine model and optimization processes must be computationally efficient without sacrificing effectiveness.
Technical Paper

A Review of Spark-Assisted Compression Ignition (SACI) Research in the Context of Realizing a Production SACI Strategy

2019-09-09
2019-24-0027
Low temperature combustion (LTC) strategies have been a keen interest in the automotive industry for over four decades since they offer improved fuel efficiency compared to conventional spark-ignition (SI) engines. LTC strategies use high dilution to keep combustion temperatures below about 2000 K to reduce heat transfer losses while avoiding locally rich in-cylinder regions that produce high soot. High dilution also enables an efficiency improvement from reduced pumping work and improved thermodynamic properties, though it requires high ignition energy. Combustion can be achieved by triggering autoignition from compression energy. High compression ratios are typically required to produce this level of ignition energy, which further improves fuel efficiency. The timing of the autoignition event is influenced by fuel properties and mixture composition, and is exponentially sensitive to temperature.
Technical Paper

Comparison between Finite Element and Hybrid Finite Element Results to Test Data for the Vibration of a Production Car Body

2019-06-05
2019-01-1530
The Hybrid Finite Element Analysis (HFEA) method is based on combining conventional Finite Element Analysis (FEA) with analytical solutions and energy methods for mid-frequency computations. The method is appropriate for computing the vibration of structures which are comprised by stiff load bearing components and flexible panels attached to them; and for considering structure-borne loadings with the excitations applied on the load bearing members. In such situations, the difficulty in using conventional FEA at higher frequencies originates from requiring a very large number of elements in order to capture the flexible wavelength of the panel members which are present in a structure. In the HFEA the conventional FEA model is modified by de-activating the bending behavior of the flexible panels in the FEA computations and introducing instead a large number of dynamic impedance elements for representing the omitted bending behavior of the panels.
Technical Paper

Structural Vibration of an Elastically Supported Plate due to Excitation of a Turbulent Boundary Layer

2019-06-05
2019-01-1470
High-Reynolds number turbulent boundary layers are an important source for inducing structural vibration. Small geometric features of a structure can generate significant turbulence that result in structural vibration. In this work we develop a new method to couple a high-fidelity fluid solver with a dynamic hybrid analytical-numerical formulation for the structure. The fluid solver uses the Large-Eddy Simulation closure for the unresolved turbulence. Specifically, a local and dynamic one-equation eddy viscosity model is employed. The fluid pressure fluctuation on the structure is mapped to the dynamic structural model. The plate where the flow excitation is applied is considered as part of a larger structure. A hybrid approach based on the Component Mode Synthesis (CMS) is used for developing the new hybrid formulation. The dynamic behavior of the plate which is excited by the flow is modeled using finite elements.
Technical Paper

Structural-Acoustic Modeling and Optimization of a Submarine Pressure Hull

2019-06-05
2019-01-1498
The Energy Finite Element Analysis (EFEA) has been validated in the past through comparison with test data for computing the structural vibration and the radiated noise for Naval systems in the mid to high frequency range. A main benefit of the method is that it enables fast computations for full scale models. This capability is exploited by using the EFEA for a submarine pressure hull design optimization study. A generic but representative pressure hull is considered. Design variables associated with the dimensions of the king frames, the thickness of the pressure hull in the vicinity of the excitation (the latter is considered to be applied on the king frames of the machinery room), the dimensions of the frames, and the damping applied on the hull are adjusted during the optimization process in order to minimize the radiated noise in the frequency range from 1,000Hz to 16,000Hz.
Technical Paper

An Immersive Vehicle-in-the-Loop VR Platform for Evaluating Human-to-Autonomous Vehicle Interactions

2019-04-02
2019-01-0143
The deployment of autonomous vehicles in real-world scenarios requires thorough testing to ensure sufficient safety levels. Driving simulators have proven to be useful testbeds for assisted and autonomous driving functionalities but may fail to capture all the nuances of real-world conditions. In this paper, we present a snapshot of the design and evaluation using a Cooperative Adaptive Cruise Control application of virtual reality platform currently in development at our institution. The platform is designed so to: allow for incorporating live real-world driving data into the simulation, enabling Vehicle-in-the-Loop testing of autonomous driving behaviors and providing us with a useful mean to evaluate the human factor in the autonomous vehicle context.
Technical Paper

Automotive Waste Heat Recovery after Engine Shutoff in Parking Lots

2019-04-02
2019-01-0157
1 The efficiency of internal combustion engines remains a research challenge given the mechanical friction and thermodynamic losses. Although incremental engine design changes continue to emerge, the harvesting of waste heat represents an immediate opportunity to address improved energy utilization. An external mobile thermal recovery system for gasoline and diesel engines is proposed for use in parking lots based on phase change material cartridges. Heat is extracted via a retrofitted conduction plate beneath the engine block after engine shutoff. An autonomous robot attaches the cartridge to the plate and transfers the heat from the block to the Phase Change Material (PCM) and returns later to retrieve the packet. These reusable cartridges are then driven to a Heat Extraction and Recycling Tower (HEART) facility where a heat exchanger harvests the thermal energy stored in the cartridges.
Technical Paper

Analyzing and Preventing Data Privacy Leakage in Connected Vehicle Services

2019-04-02
2019-01-0478
The rapid development of connected and automated vehicle technologies together with cloud-based mobility services are revolutionizing the transportation industry. As a result, huge amounts of data are being generated, collected, and utilized, hence providing tremendous business opportunities. However, this big data poses serious challenges mainly in terms of data privacy. The risks of privacy leakage are amplified by the information sharing nature of emerging mobility services and the recent advances in data analytics. In this paper, we provide an overview of the connected vehicle landscape and point out potential privacy threats. We demonstrate two of the risks, namely additional individual information inference and user de-anonymization, through concrete attack designs. We also propose corresponding countermeasures to defend against such privacy attacks. We evaluate the feasibility of such attacks and our defense strategies using real world vehicular data.
Technical Paper

Survey of Automotive Privacy Regulations and Privacy-Related Attacks

2019-04-02
2019-01-0479
Privacy has been a rising concern. The European Union has established a privacy standard called General Data Protection Regulation (GDPR) in May 2018. Furthermore, the Facebook-Cambridge Analytica data incident made headlines in March 2018. Data collection from vehicles by OEM platforms is increasingly popular and may offer OEMs new business models but it comes with the risk of privacy leakages. Vehicular sensor data shared with third-parties can lead to misuse of the requested data for other purposes than stated/intended. There exists a relevant regulation document introduced by the Alliance of Automobile Manufacturers (“Auto Alliance”), which classifies the vehicular sensors used for data collection as covered and non-sensitive parameters.
Technical Paper

Strain Rate Effect on Martensitic Transformation in a TRIP Steel Containing Carbide-Free Bainite

2019-04-02
2019-01-0521
Adiabatic heating during plastic straining can slow the diffusionless shear transformation of austenite to martensite in steels that exhibit transformation induced plasticity (TRIP). However, the extent to which the transformation is affected over a strain rate range of relevance to automotive stamping and vehicle impact events is unclear for most third-generation advanced high strength TRIP steels. In this study, an 1180MPa minimum tensile strength TRIP steel with carbide-free bainite is evaluated by measuring the variation of retained austenite volume fraction (RAVF) in fractured tensile specimens with position and strain. This requires a combination of servo-hydraulic load frame instrumented with high speed stereo digital image correlation for measurement of strains and ex-situ synchrotron x-ray diffraction for determination of RAVF in fractured tensile specimens.
Technical Paper

Prediction of Human Actions in Assembly Process by a Spatial-Temporal End-to-End Learning Model

2019-04-02
2019-01-0509
It’s important to predict human actions in the industry assembly process. Foreseeing future actions before they happened is an essential part for flexible human-robot collaboration and crucial to safety issues. Vision-based human action prediction from videos provides intuitive and adequate knowledge for many complex applications. This problem can be interpreted as deducing the next action of people from a short video clip. The history information needs to be considered to learn these relations among time steps for predicting the future steps. However, it is difficult to extract the history information and use it to infer the future situation with traditional methods. In this scenario, a model is needed to handle the spatial and temporal details stored in the past human motions and construct the future action based on limited accessible human demonstrations.
Technical Paper

Design of a Portable Thermoelectric Convective Cooling System for Neighborhood Electric Vehicles and Other Applications

2019-04-02
2019-01-0499
Automotive technology is increasingly reliant on electrically driven accessories, systems, and payloads thanks to the rising popularity of electric and hybrid electric vehicles. Solid state and similar purely electrical solutions such as thermoelectric devices are eminently preferable sources for thermal management in neighborhood electric vehicles (NEVs) and similar short-range automobiles which often do not come stock with a climate control system. Directed convection strategies such as zone cooling using DC electric current are a natural fit for the infinitely scalable thermal control architecture possible with thermoelectrics. One such prototype device, actuated by thermoelectric devices, has been developed to meet a variety of thermal management needs with a versatile, portable system suitable for NEVs, micro cars without air conditioning, or even more specialized cooling needs.
Technical Paper

Sensations Associated with Motion Sickness Response during Passenger Vehicle Operations on a Test Track

2019-04-02
2019-01-0687
Motion sickness in road vehicles may become an increasingly important problem as automation transforms drivers into passengers. The University of Michigan Transportation Research Institute has developed a vehicle-based platform to study motion sickness in passenger vehicles. A test-track study was conducted with 52 participants who reported susceptibility to motion sickness. The participants completed in-vehicle testing on a 20-minute scripted, continuous drive that consisted of a series of frequent 90-degree turns, braking, and lane changes at the U-M Mcity facility. In addition to quantifying their level of motion sickness on a numerical scale, participants were asked to describe in words any motion-sickness-related sensations they experienced.
Technical Paper

Modeling and Learning of Object Placing Tasks from Human Demonstrations in Smart Manufacturing

2019-04-02
2019-01-0700
In this paper, we present a framework for the robot to learn how to place objects to a workpiece by learning from humans in smart manufacturing. In the proposed framework, the rational scene dictionary (RSD) corresponding to the keyframes of task (KFT) are used to identify the general object-action-location relationships. The Generalized Voronoi Diagrams (GVD) based contour is used to determine the relative position and orientation between the object and the corresponding workpiece at the final state. In the learning phase, we keep tracking the image segments in the human demonstration. For the moment when a spatial relation of some segments are changed in a discontinuous way, the state changes are recorded by the RSD. KFT is abstracted after traversing and searching in RSD, while the relative position and orientation of the object and the corresponding mount are presented by GVD-based contours for the keyframes.
Technical Paper

A Voice and Pointing Gesture Interaction System for On-Route Update of Autonomous Vehicles’ Path

2019-04-02
2019-01-0679
This paper describes the development and simulation of a voice and pointing gesture interaction system for on-route update of autonomous vehicles’ path. The objective of this research is to provide users of autonomous vehicles a human vehicle interaction mode that enables them to make and communicate spontaneous decisions to the autonomous car, modifying its pre-defined autonomous route in real-time. For example, similar to giving directions to a taxi driver, a user will be able to tell the car «Stop there» or «Take that exit». In this way, the user control/spontaneity vs interaction flexibility dilemma that current autonomous vehicle concepts have, could be solved, potentially increasing the user acceptance of this technology. The system was designed following a level structured state machine approach. The simulations were developed using MATLAB and VREP, a robotics simulation platform, which has accurate vehicle and sensor models.
Technical Paper

Use of Machine Learning for Real-Time Non-Linear Model Predictive Engine Control

2019-04-02
2019-01-1289
Non-linear model predictive engine control (nMPC) systems have the ability to reduce calibration effort while improving transient engine response. The main drawback of nMPC for engine control is the computational power required to realize real-time operation. Most of this computational power is spent linearizing the non-linear plant model at each time step. Additionally, the effectiveness of the nMPC system relies heavily on the accuracy of the model(s) used to predict the future system behavior, which can be difficult to model physically. This paper introduces a hybrid modeling approach for internal combustion engines that combines physics-based and machine learning techniques to generate accurate models that can be linearized with low computational power. This approach preserves the generalization and robustness of physics-based models, while maintaining high accuracy of data-driven models. Advantages of applying the proposed model with nMPC are discussed.
Technical Paper

Development of an Alternative Predictive Model for Gasoline Vehicle Particulate Matter and Particulate Number

2019-04-02
2019-01-1184
The Particulate Matter Index (PMI) is a helpful tool which provides an indication of a fuel’s sooting tendency. Currently, the index is being used by various laboratories and OEMs as a metric to understand the gasoline fuels impact on both sooting found on engine hardware and vehicle out emissions. This paper will explore a new method that could be used to give indication of the sooting tendency of the gasoline range fuels, called the Particulate Evaluation Index (PEI), and provide the detailed equation in its initial form. In addition, the PEI will be shown to have a good correlation agreement to PMI. The paper will then give a detailed explanation of the data used to develop it. Initial vehicle PM/PN data will also be presented that shows correlations of the indices to the vehicle response.
Technical Paper

Equivalent Consumption Minimization Strategy for a Power Split Supercharger

2019-04-02
2019-01-1207
Low voltage hybridization (<60 V) supports engine start/stop, regenerative braking, and constrained torque assist/regeneration at a low cost. This work studies the potential benefits of a novel hybrid system, called a power split supercharger (PSS). A 9 kW motor is shared between boosting the engine or providing hybrid functionalities, allowing it to couple with a small engine and still support good acceleration. However, the PSS operation is limited to only one of the parallel hybrid or boosting modes at each time instance. In this work an equivalent consumption minimization strategy (ECMS) is developed to select the PSS mode and the motor torque during hybrid mode. The PSS operation is simulated over standard EPA drive cycles with an engine mean value model that captures detailed air path and PSS dynamics.
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