Search Results

In this paper, residual stress distributions in rectangular bars due to rolling or burnishing at very high rolling or burnishing loads are investigated by roll burnishing experiments and three-dimensional finite element analyses using ABAQUS. First, roll burnishing experiments on rectangular bars at two roller burnishing loads are presented. The results indicate the higher burnishing load induces lower residual stresses and the higher burnishing load does not improve fatigue lives. Next, in the corresponding finite element analyses, the roller is modeled as rigid and the roller rolls on the flat surface of the bar with a low coefficient of friction. The bar material is modeled as an elastic-plastic strain hardening material with a nonlinear kinematic hardening rule for loading and unloading.

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.

It is estimated that operating continuously on a B20 fuel containing the current allowable ASTM specification limits for metal impurities in biodiesel could result in a doubling of ash exposure relative to lube-oil-derived ash. The purpose of this study was to determine if a fuel containing metals at the ASTM limits could cause adverse impacts on the performance and durability of diesel emission control systems. An accelerated durability test method was developed to determine the potential impact of these biodiesel impurities. The test program included engine testing with multiple DPF substrate types as well as DOC and SCR catalysts. The results showed no significant degradation in the thermo-mechanical properties of cordierite, aluminum titanate, or silicon carbide DPFs after exposure to 150,000 mile equivalent biodiesel ash and thermal aging. However, exposure of a cordierite DPF to 435,000 mile equivalent aging resulted in a 69% decrease in the thermal shock resistance parameter.

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.

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.

In order to further characterize and optimize the performance of Selective Catalytic Reduction (SCR) aftertreatment systems used on heavy-duty diesel engines, an accurately calibrated high-fidelity multi-step global kinetic SCR model and a reduced order estimator for on-board diagnostic (OBD) and control are desirable. In this study, a Cu-zeolite SCR catalyst from a 2010 Cummins ISB engine was experimentally studied in a flow reactor using carefully designed protocols. A 2-site SCR model describing mass transfer and the SCR chemical reaction mechanisms is described in the paper. The model was calibrated to the reactor test data sets collected under temperatures from 200 to 425 °C and SCR space velocities of 60000, 90000, and 120000 hr-1. The model parameters were calibrated using an optimization code to minimize the error between measured and simulated NO, NO₂, N₂O, and NH₃ gas concentration time histories.

With stringent emission regulations, aftertreatment systems with a Diesel Particulate Filter (DPF) and a Selective Catalytic Reduction (SCR) are required for diesel engines to meet PM and NOx emissions. The adoption of aftertreatment increases the back pressure on a typical diesel engine and makes engine calibration a complicated process, requiring thousands of steady state testing points to optimize engine performance. When configuring an engine to meet Tier IV final emission regulations in the USA or corresponding Stage IV emission regulations in Europe, this high back pressure dramatically impacts transient performance. The peak NOx, smoke and exhaust temperature during a diesel engine transient cycle, such as the Non-Road Transient Cycle (NRTC) defined by the US Environmental Protection Agency (EPA), will in turn affect the performance of the aftertreatment system and the tailpipe emissions level.

The growth of auto sales in emerging markets provides a good opportunity for automakers. Cost is a key factor for any automaker to win in an emerging market. This paper analyzes risks and opportunities in a low cost manufacturing environment. The Chinese auto market is used as an example and three categories of risks are analyzed. A typical risk assessment for cost reduction includes the analysis of environment risks, process risks and strategic risks associated with all phases of a product life. In an emerging market, emission regulations are a rapidly-evolving environment variable, since most countries with less regulated emission codes try to catch up with the newly- developed technologies to meet sustainable growth targets. Emission regulations have a huge impact on product design, manufacturing and maintenance in the automotive industry, and hence the related cost reduction must be thoroughly analyzed during risk assessment.

Various engine platforms employ Selective Catalytic Reduction (SCR) technology to reduce the tail pipe emissions of oxides of nitrogen (NOx) from diesel engines as part of an overall strategy to comply with the emission regulations in place in various countries. High levels of NOx conversion (greater than 98%) in SCR aftertreatment may provide operating margin to increase overall fuel efficiency. However, to realize the potential fuel efficiency gains, the SCR technology employed should achieve high NOx conversion with limited reductant slip over transient application cycles in addition to steady state operation. A new approach to SCR controls was developed and implemented. This approach does not rely on any maps to determine the amount of urea solution to be dosed, thus significantly reducing calibration and development time and effort when implementing the SCR technology on multiple engine platforms and applications.

NOx reduction efficiency in simulated lean exhaust conditions has been examined for three proprietary catalyst materials using a non-thermal plasma discharge as a pretreatment stage to the catalyst. Using propene as the reducing agent for selective catalytic reduction, 74% reduction of NOx has been observed in the presence of 20 ppm SO2. For sulfur-free simulated exhaust, 84% NOx reduction has been obtained. Results show that the impact of sulfur on the samples examined can vary widely from virtually no effect (< 5%) to more than 20% loss in activity depending on the catalyst. Any loss due to sulfur poisoning appears to be irreversible according to limited measurements on poisoned catalysts exposed to sulfur-free exhaust streams. Catalysts were tested over a temperature range of 473-773K, with the highest activity observed at 773K. Examination of this large temperature window has shown that the optimum C1:NOx ratio changes with temperature.

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.

Fuel properties impact the engine-out emission directly. For some geographic regions where diesel engines can meet emission regulations without aftertreatment, the change of fuel properties will lead to final tailpipe emission variation. Aftertreatment systems such as Diesel Particulate Filter (DPF) and Selective Catalytic Reduction (SCR) are required for diesel engines to meet stringent regulations. These regulations include off-road Tier 4 Final emission regulations in the USA or the corresponding Stage IV emission regulations in Europe. As an engine with an aftertreatment system, the change of fuel properties will also affect the system conversion efficiency and regeneration cycle. Previous research works focus on prediction of engine-out emission, and many are based on chemical reactions. Due to the complex mixing, pyrolysis and reaction process in heterogeneous combustion, it is not cost-effective to find a general model to predict emission shifting due to fuel variation.