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This manuscript provides a review of different types and categorization of the chassis dynamometer systems. The review classifies the chassis dynamometers based on the configuration, type of rollers and the application type. Additionally the manuscript discusses several application examples of the chassis dynamometer including: performance and endurance mileage accumulation tests, fuel efficiency and exhaust emissions, noise, vibration and harshness testing (NVH). Different types of the vehicle attachment system in the dynamometer cell and its influences on the driving force characteristics and the vehicle acoustic signature is also discussed. The text also highlights the impact of the use of the chassis dynamometer as a development platform and its impact on the development process. Examples of using chassis dynamometer as a development platform using Vehicle Hardware In-the-Loop (VHiL) approach including drivability assessment and transmission calibrations are presented.

The use of Low Pressure - Exhaust Gas Recirculation (EGR) is intended to allow displacement reduction in turbocharged gasoline engines and improve fuel economy. Low Pressure EGR designs have an advantage over High Pressure configurations since they interfere less with turbocharger efficiency and improve the uniformity of air-EGR mixing in the engine. In this research, Low Pressure (LP) cooled EGR is evaluated on a turbocharged direct injection gasoline engine with variable valve timing using both simulation and experimental results. First, a model-based calibration study is conducted using simulation tools to identify fuel efficiency gains of LP EGR over the base calibration. The main sources of the efficiency improvement are then quantified individually, focusing on part-load de-throttling of the engine, heat loss reduction, knock mitigation as well as decreased high-load fuel enrichment through exhaust temperature reduction.

This research proposes a control system for Spark Ignition (SI) engines with external Exhaust Gas Recirculation (EGR) based on model predictive control and a disturbance observer. The proposed Economic Nonlinear Model Predictive Controller (E-NMPC) tries to minimize fuel consumption for a number of engine cycles into the future given an Indicated Mean Effective Pressure (IMEP) tracking reference and abnormal combustion constraints like knock and combustion variability. A nonlinear optimization problem is formulated and solved in real time using Sequential Quadratic Programming (SQP) to obtain the desired control actuator set-points. An Extended Kalman Filter (EKF) based observer is applied to estimate engine states, combining both air path and cylinder dynamics. The EKF engine state(s) observer is augmented with disturbance estimation to account for modeling errors and/or sensor/actuator offset.

This paper discusses a compliant link suspension concept developed for use on a high performance automobile. This suspension uses compliant or flexible members to integrate energy storage and kinematic guidance functions. The goal of the design was to achieve similar elasto-kinematic performance compared to a benchmark OEM suspension, while employing fewer components and having reduced mass and complexity, and potentially providing packaging advantages. The proposed suspension system replaces a control arm in the existing suspension with a ternary supported compliant link that stores energy in bending during suspension vertical motion. The design was refined iteratively by using a computational model to simulate the elasto-kinematic performance as the dimensions and attachment point locations of the compliant link were varied, until the predicted performance closely matched the performance of the benchmark suspension.

This paper is a review of turbulence models and computational methods that have been produced at Clemson University's Advanced Computational Research Laboratory. The goal of the turbulence model development has been to create physics-based models that are economically feasible and can be used in a competitive environment, where turnaround time is a critical factor. Given this goal, all of the work has been focused on Reynolds-Averaged Navier-Stokes (RANS) simulations in the eddy-viscosity framework with the majority of the turbulence models having three transport equations in addition to mass, momentum, and energy. Several areas have been targeted for improvement in turbulence modeling for complex flows such as those found in motorsports aerodynamics: the effects of streamline curvature and rotation on the turbulence field, laminar-turbulent transition, and separated shear layer rollup and breakdown.

The Three Way Catalyst (TWC) is an effective pollutant conversion system widely used in current production vehicles to satisfy emissions regulations. A TWC’s conversion efficiency degrades over time due to chemical and/or thermal mechanisms causing the catalyst to age. This reduction in conversion efficiency must be accounted for to ensure full useful life emissions compliance. This paper presents an experimental study of the aging impact on TWC performance. Four TWCs differentiated by their age, given in terms of miles driven, were tested. It is shown that the dynamics of oxygen storage are substantially affected by aging of the TWC. A previously developed physics-based oxygen storage model [1] is subsequently used to incorporate the effect of aging on the total Oxygen Storage Capacity (OSC). Parameter identification results for the different age catalysts show that total oxygen storage capacity decreases substantially with aging and is insensitive to operating conditions.

Accurate in-cylinder air charge estimation is important for engine torque determination, controlling air-to-fuel ratio, and ensuring high after-treatment efficiency. Spark ignition (SI) engine technologies like variable valve timing (VVT) and exhaust gas recirculation (EGR) are applied to improve fuel economy and reduce pollutant emissions, but they increase the complexity of air charge estimation. Increased air-path complexity drives the need for cost effective solutions that produce high air mass prediction accuracy while minimizing sensor cost, computational effort, and calibration time. A large number of air charge estimation techniques have been developed using a range of sensors sets combined with empirical and/or physics-based models. This paper provides a technical review of research in this area, focused on SI engines.

Low-pressure cooled EGR (LP-cEGR) systems can provide significant improvements in spark-ignition engine efficiency and knock resistance. However, open-loop control of these systems is challenging due to low pressure differentials and the presence of pulsating flow at the EGR valve. This research describes a control structure for Low-pressure cooled EGR systems using closed loop feedback control along with internal model control. A Smith Predictor based PID controller is utilized in combination with an intake oxygen sensor for feedback control of EGR fraction. Gas transport delays are considered as dead-time delays and a Smith Predictor is one of the conventional methods to address stability concerns of such systems. However, this approach requires a plant model of the air-path from the EGR valve to the sensor.

Low pressure (LP) and cooled EGR systems are capable of increasing fuel efficiency of turbocharged gasoline engines, however they introduce control challenges. Accurate exhaust pressure modeling is of particular importance for real-time feedforward control of these EGR systems since they operate under low pressure differentials. To provide a solution that does not depend on physical sensors in the exhaust and also does not require extensive calibration, a coupled temperature and pressure physics-based model is proposed. The exhaust pipe is split into two different lumped sections based on flow conditions in order to calculate turbine-outlet pressure, which is the driving force for LP-EGR. The temperature model uses the turbine-outlet temperature as an input, which is known through existing engine control models, to determine heat transfer losses through the exhaust.

A new approach to lightweight engineering of vehicles focuses on identifying and eliminating Lazy Parts through the application of the Lazy Parts Indication Method (LPIM). In this context, Lazy Parts are defined as components that have the potential for mass reduction for a number of reasons discussed in previous literature. The focus of this research is to apply the LPIM to an automotive component, identify potential mass savings, and redesign the component to address the laziness and begin to validate the LPIM as well at the estimated mass savings. A generator mounting bracket for a vehicle is analyzed using the LPIM and redesigned. The application of the LPIM to the generator mounting bracket predicted an estimated mass savings of 10% (0.32kg), while the actual redesign of the bracket revealed a 12% (0.38kg) mass savings.

Knock-limited engine operation is one of the most important constraints on fuel efficiency and performance that must be considered during the design, control algorithm development and calibration of spark-ignition engines. This research evaluates the accuracy of model-based knock prediction routines and their applicability for control-oriented applications over various engine operating conditions using commercial fuels. Two common methods of knock prediction, a generalized chemical kinetics model and an empirical induction-time correlation, are evaluated and compared against experimental data. The experimental investigation is conducted using a naturally aspirated 3.6L V6 engine, retrofitted with cooled Exhaust Gas Recirculation (EGR). Data are acquired from spark timing sweeps under knocking conditions at different engine speeds and loads in an engine dynamometer cell.

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.

Fuel efficiency improvement in automobiles has been a topic of great interest over the past few years, especially with the introduction of the new CAFE 2025 standards. Although there are multiple ways of improving the fuel efficiency of an automobile, lightweighting is one of the most common approaches taken by many automotive manufacturers. Lightweighting is even more significant in electric vehicles as it directly affects the range of the vehicle. Amidst this context of lightweighting, the use of composite materials as alternatives to metals has been proven in the past to help achieve substantial weight reduction. The focus of using composites for weight reduction has however been typically limited to major structural components, such as BiW and closures, due to high material costs. Secondary structural components which contribute approximately 30% of the vehicle weight are usually neglected by these weight reduction studies.

Vehicle lightweighting has been a constant theme of research at numerous Original Equipment Manufacturers (OEM’s) as it provides one of the best opportunities for improving fuel efficiency. In this regard, the Department of Energy (DOE) Vehicle Technology Office set a challenge to lightweight a fully assembled driver’s side front door by at least 42.5% with the cost constraint of a maximum $5 increase for every pound saved. A baseline door of an OEM’s 2014 mid-size SUV was selected, and an integrated design, analysis, and optimization approach was implemented to meet this goal. The ultra-lightweight door design had to meet or exceed the fit & function and mechanical performance (static and dynamic) of the baseline door while being suitable for mass production. The design strategy involved parts consolidation, and multi-material distribution to enable mass reduction without compromising the fit and functional requirements.

Catalytic converters, which are commonly used for after-treatment in SI engines, exhibit poor performance at lower temperatures. This is one of the main reasons that tailpipe emissions drastically increase during cold-start periods. Thermal inertia of turbocharger casing prolongs the catalyst warm-up time. Exhaust enthalpy management becomes crucial for a turbocharged direct injection spark ignition (DISI) engine during cold-start periods to quickly heat the catalyst and minimize cold-start emissions. Thermal barrier coatings (TBCs), because of their low thermal inertia, reach higher surface temperatures faster than metal walls, thereby blocking heat transfer and saving enthalpy for the catalyst. The TBCs applied on surfaces that exchange heat with exhaust gases can increase the enthalpy available for the catalyst warm-up.

The duration over which a three way catalyst (TWC) maintains proper functionality during lambda excursions is critically impacted by aging, which affects its oxygen storage capacity (OSC). As such, emissions control strategies, which strive to maintain post TWC air-to-fuel ratios at the stoichiometric value, will benefit from an accurate estimation of TWC age. To this end, this investigation examines a method of TWC age estimation suitable for real-world transient operation. Experimental results are harvested from an instrumented test vehicle equipped with a two-brick TWC during operation on a chassis dynamometer. Four differently aged TWCs are instrumented with wideband and switch-type Lambda sensors upstream (Pre TWC location), and downstream (Mid location) of first catalyst brick.

In this paper, we review the literature related to the reuse of computer-based simulation models in the context of systems design. Models are used to capture aspects of existing or envisioned systems and are simulated to predict the behavior of these systems. However, developing such models from scratch requires significant time and effort. Researchers have recognized that the time and effort can be reduced if existing models or model components are reused, leading to the study of model reusability. In this paper, we review the tasks necessary to retrieve and reuse model components from repositories, and to prepare new models and model components such that they are more amenable for future reuse. Model reuse can be significantly enhanced by carefully characterizing the model, and capturing its meaning and intent so that potential users can determine whether the model meets their needs.