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Autonomous vehicle operation is dependent upon accurate position estimation and thus a major concern of implementing the autonomous navigation is obtaining robust and accurate data from sensors. This is especially true, in case of Inertial Measurement Unit (IMU) sensor data. The IMU consists of a 3-axis gyro, 3-axis accelerometer, and 3-axis magnetometer. The IMU provides vehicle orientation in 3D space in terms of yaw, roll and pitch. Out of which, yaw is a major parameter to control the ground vehicle’s lateral position during navigation. The accelerometer is responsible for attitude (roll-pitch) estimates and magnetometer is responsible for yaw estimates. However, the magnetometer is prone to environmental magnetic disturbances which induce errors in the measurement.

In this paper, a model-based linear estimator and a non-linear control law for an Fe-zeolite urea-selective catalytic reduction (SCR) catalyst for heavy duty diesel engine applications is presented. The novel aspect of this work is that the relevant species, NO, NO2 and NH3 are estimated and controlled independently. The ability to target NH3 slip is important not only to minimize urea consumption, but also to reduce this unregulated emission. Being able to discriminate between NO and NO2 is important for two reasons. First, recent Fe-zeolite catalyst studies suggest that NOx reduction is highly favored by the NO 2 based reactions. Second, NO2 is more toxic than NO to both the environment and human health. The estimator and control law are based on a 4-state model of the urea-SCR plant. A linearized version of the model is used for state estimation while the full nonlinear model is used for control design.

This paper studies the hardware-in-the-loop (HiL) design of a power-split hybrid electric vehicle (HEV) for the research of HEV lithiumion battery aging. In this paper, an electrochemical model of a lithium-ion battery pack with the characteristics of battery aging is built and integrated into the vehicle model of Autonomie® software from Argonne National Laboratory. The vehicle model, together with the electrochemical battery model, is designed to run in a dSPACE real-time simulator while the powertrain power distribution is managed by a dSPACE MicroAutoBoxII hardware controller. The control interface is designed using dSPACE ControlDesk to monitor the real-time simulation results. The HiL simulation results with the performance of vehicle dynamics and the thermal aging of the battery are presented and analyzed.

This paper presents an overview of the connected controls and optimization system for vehicle dynamics and powertrain operation on a light-duty plug-in multi-mode hybrid electric vehicle developed as part of the DOE ARPA-E NEXTCAR program by Michigan Technological University in partnership with General Motors Co. The objective is to enable a 20% reduction in overall energy consumption and a 6% increase in electric vehicle range of a plug-in hybrid electric vehicle through the utilization of connected and automated vehicle technologies. Technologies developed to achieve this goal were developed in two categories, the vehicle control level and the powertrain control level. Tools at the vehicle control level include Eco Routing, Speed Harmonization, Eco Approach and Departure and in-situ vehicle parameter characterization.

A computational analysis of underbody windnoise sources on a production automobile at 180 km/h free stream air speed and 0° yaw is presented. Two different underbody geometry configurations were considered for this study. The numerical results have been obtained using the commercial software PowerFLOW. The simulation kernel of this software is based on the numerical scheme known as the Lattice-Boltzmann Method (LBM), combined with a two-equation RNG turbulence model. This scheme accurately captures time-dependent aerodynamic behavior of turbulent flows over complex detailed geometries, including the pressure fluctuations causing wind noise. Comparison of pressure fluctuations levels mapped on a fluid plane below the underbody shows very good correlation between experiment and simulation. Detailed flow analysis was done for both configurations to obtain insight into the transient nature of the flow field in the underbody region.

Currently, the aerodynamic development of a car concentrates on steady state aerodynamic forces. Development is mainly performed in wind tunnels with very low turbulence. On the road we find other boundary conditions. Natural wind, other cars and trucks influence the yawing moment and the side force. During acceleration and deceleration the vehicle speed is not constant, the effect of unsteady aerodynamic forces is especially important and can not be neglected. The approach to measure unsteady effects is to use a wind tunnel that has the capability to produce unsteady flow and in addition to instrument a car to drive under natural windy conditions. The wind tunnel, with its reproducible conditions, allows measurements to be made with well defined frequencies of the approaching flow. This is important since the aerodynamic forces are not sensitive to all frequencies in the same way. One way to increase driving comfort is to reduce these forces at specific frequencies.

Model-based control strategies are important for meeting the dual objective of maximizing NOx reduction and minimizing NH3 slip in urea-SCR catalysts. To be implementable on the vehicle, the models should capture the essential behavior of the system, while not being computationally intensive. This paper discusses the adequacy of two different reduced order SCR catalyst models and compares their performance with a higher order model. The higher order model assumes that the catalyst has both diffusion and reaction kinetics, whereas the reduced order models contain only reaction kinetics. After describing each model, its parameter identification and model validation based on experiments on a Navistar I6 7.6L engine are presented. The adequacy of reduced order models is demonstrated by comparing the NO, NO2 and NH3 concentrations predicted by the models to their concentrations from the test data.

Underbody aerodynamics has become increasingly important over the last three decades because of its vital contribution to improving a vehicle's overall performance. This was the motivation for the research conducted by BMW Aerodynamics, concerning the determination of the overall pressure distribution on the underbody of a series-production vehicle. Static pressure measurements have been taken under various test conditions. Real on-road tests were carried out as well as wind tunnel experiments under application of different road simulation techniques. The analyzed vehicle configurations include wheel rim-tire and body modifications. The results presented include surface pressure data, drag and lift coefficients, ride heights, pitch and roll angles. The acquired data is used to examine the underbody flow topology and determine how the diverse attempts to represent the real on-road conditions affect its pressure distribution.

While hybrid-electric powertrain features such as regenerative braking and electric driving can improve the fuel economy of a vehicle significantly, these features may also have a considerable impact on driving dynamics. That is why extra effort is necessary to ensure safety and comfort that customers usually expect from a conventional vehicle. The purpose of this paper is to initiate a discussion regarding different drivetrain concepts, necessary changes in chassis systems, and the impact on vehicle dynamics. To provide input to this essential discussion, braking and steering systems, as well as suspension design, are analyzed regarding their fit with hybrid systems. It is shown how an integration of hybrid technology and chassis systems benefits vehicle dynamics and why “by-wire” technology is a key enabler for safe and comfortable hybrid-electric vehicles.

Unsteady aerodynamic flow phenomena are investigated in the wind tunnel by oscillating a realistic 50% scale model around its vertical axis. Thus the model is exposed to time-dependent flow conditions at realistic Reynolds and Strouhal numbers. Using this setup unsteady aerodynamic loads are observed to differ significantly from quasi-steady loads. In particular, the unsteady yaw moment exceeds the quasi-steady approximation by 80%. On the other hand, side force and roll moment are over predicted by quasi-steady approximation but exhibit a significant time delay. Using hotwire anemometry, a delayed reaction of the wake flow of Δt/T = 0.15 is observed, which is thought to be the principal cause for the differences between unsteady and quasi-steady aerodynamic loads. A schematic mechanism explaining these differences due to the delayed reaction of the wake flow is proposed.

Unsteady aerodynamic flow phenomena are investigated in a wind tunnel by oscillating a realistic 50% scale model around the vertical axis. Thus the model is exposed to time-dependent flow conditions at realistic Reynolds and Strouhal numbers. Using this setup unsteady aerodynamic loads are observed to differ significantly from quasi steady loads. In particular, the unsteady yaw moment exceeds the quasi steady approximation significantly. On the other hand, side force and roll moment are over predicted by quasi steady approximation but exhibit a significant time delay. Part 2 of this study proves that a delayed and enhanced response of the surface pressures at the rear side of the vehicle is responsible for the differences between unsteady and quasi steady loads. The pressure changes at the vehicle front, however, are shown to have similar amplitudes and almost no phase shift compared to quasi steady flow conditions.

When a manual transmission (MT) powertrain is subjected to high speeds and high torques, the vehicle driveshaft, and other components experience an increase in stored potential energy. When the engine and driveshaft are decoupled during an up or down shift, the potential energy is released causing clunk during the shift event. The customer desires a smooth shift thus reduction of clunk will improve experience and satisfaction. In this study, a six-speed MT, rear-wheel-drive (RWD) passenger vehicle was used to experimentally capture acoustic and vibration data during the clunk event. To replicate the in-situ results, additional data was collected and analyzed for powertrain component roll and pitch. A lumped parameter model of key powertrain components was created to replicate the clunk event and correlate with test data. The lumped parameter model was used to modify clutch tip-out parameters, which resulted in reduced prop shaft oscillations.

Measurements from a Global Navigation System in conjunction with an Inertial Measurement Unit were recently introduced in different aerial and ground vehicles as an input to control vehicle dynamics. In automobiles this approach could help to further improve braking and / or stability control systems as information like velocity over ground and side slip angle becomes available. This paper presents the technical background, validation through test results and the evaluation of potential benefits of such an “INS/GPS” setup. As a result of the extended measuring capabilities a reduction in braking distance and a more effective stability control becomes possible. The results show an excellent performance that should be exploited in future automotive applications.

A top-of-the-range car customer not only expects exceptional vehicle design and quality but also a driving experience, which is out of the ordinary. Very harmonious interaction between vehicle dynamics and the steering system is required to offer clients such a consistent driving experience through generations of vehicle models. In this paper the basic properties of a premium driving experience are explored. It is shown that outstanding handling limits are a prerequisite, although most customers never experience such driving situations. In fact, on-center behavior is most crucial in enabling clients to experience part of premium driving performance, and the steering system is the key factor in delivering appropriate feedback to the driver by means of steering torque. Development procedures are presented to achieve the goals described above.

A practical approach for evaluating and validating global system designs for Squeak and Rattle performance is proposed. Using simple slip and rattle models, actual sound and vibration data, and the fundamentals of audiological perception, analysis tools adapted from Chaos Theory are used to establish threshold levels of performance and identify system characteristics which are significant contributors to Squeak and Rattle. Focus on system design is maintained by using a simple rattle noise indicator and relating rattle events to levels of dynamic motion (acceleration, velocity, etc.). The threshold level is defined as the level of acceleration at which the system moves from a non-rattling state to a rattling state. The approach is demonstrated with a simple analytical model applied to an experimental structure under dynamic load.

This paper presents a methodology to optimize the blending of charge-depleting (CD) and charge-sustaining (CS) modes in a multi-mode plug-in hybrid electric vehicle (PHEV) that reduces overall energy consumption when the selected route cannot be completely driven in all-electric mode. The PHEV used in this investigation is the second-generation Chevrolet Volt and as many as four instrumented vehicles were utilized simultaneously on road to acquire validation data. The optimization method used is dynamic programming (DP) paired with a reduced-order powertrain model to enable onboard embedded controller compatibility and computational efficiency in optimally blending CD, CS modes over the entire drive route.

The Electronic Control Unit (ECU) of an Electric Power Steering (EPS) system is a core device to decide how much assistance an electric motor applies on a steering wheel. The EPS ECU plays an important role in EPS systems. The effectiveness of an ECU needs to be thoroughly tested before mass production. Hardware-in-the-loop simulation provides an efficient way for the development and testing of embedded controllers. This paper focuses on the development of a HiL system for testing EPS controllers. The hardware of the HiL system employs a dSPACE HiL simulator. The EPS plant model is an integrated model consisting of a Vehicle Dynamics model of the dSPACE Automotive Simulation Model (ASM) and the Nexteer Steering model. The paper presents the design of an EPS HiL system, the simulation of sensors and actuators, the functions of the ASM Vehicle Dynamics model, and the integration method of the ASM Vehicle Dynamics model with a Steering model.