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The reduction of automotive emissions is instrumental in the fight against air pollution and its impact on global warming. This realization has empowered governments around the world to mandate lower levels of vehicle emissions requiring the Original Equipment Manufacturers (OEMs) to implement advanced aftertreatment technologies in their applications. Achieving emission levels as low as SULEV30 or SULEV20 would have been impossible only a couple of decades ago, however, these lower levels of emissions are now a possibility through advanced control strategies and aftertreatment systems. As a part of this mandate to lower emissions, OEMs are also continuously monitoring the health and performance of their aftertreatment and control components. The implementation of On Board Diagnostics (OBD) ensures that control systems are functioning robustly and the emission levels are achieved and maintained to high mileages for the life of the vehicle.

Engine air induction shell noise is a structure borne noise that radiates from the surface of the air induction system. The noise is driven by pulsating engine induction air and is perceived as annoying by vehicle passengers. The problem is aggravated by the vehicle design demands for low weight components packaged in an increasingly tight under hood environment. Shell noise problems are often not discovered until production intent parts are available and tested on the vehicle. Part changes are often necessary which threatens program timing. Shell noise should be analyzed in the air induction system design phase and a good shell noise analytical process and targets must be defined. Several air induction clean side ducts are selected for this study. The ducts shell noise is assessed in terms of material strength and structural stiffness. A measurement process is developed to evaluate shell noise of the air induction components. Noise levels are measured inside of the clean side ducts.

One of the first steps in powertrain design is to assess its best performance and consumption in a virtual phase. Regarding hybrid electric vehicles (HEVs), it is important to define the best mode profile through a cycle in order to maximize fuel economy. To assist in that task, several off-line optimization algorithms were developed, with Dynamic Programming (DP) being the most common one. The DP algorithm generates the control actions that will result in the most optimal fuel economy of the powertrain for a known driving cycle. Although this method results in the global optimum behavior, the DP tool comes with a high computational cost. The charge-sustaining requirement and the necessity of capturing extremely small variations in the battery state of charge (SOC) makes this state vector an enormous variable. As things move fast in the industry, a rapid tool with the same performance is required.

Due to magnesium alloy's poor weldability, other joining techniques such as laser assisted self-piercing rivet (LSPR) are used for joining magnesium alloys. This research investigates the fatigue performance of LSPR for magnesium alloys including AZ31 and AM60. Tensile-shear and coach peel specimens for AZ31 and AM60 were fabricated and tested for understanding joint fatigue performance. A structural stress - life (S-N) method was used to develop the fatigue parameters from load-life test results. In order to validate this approach, test results from multijoint specimens were compared with the predicted fatigue results of these specimens using the structural stress method. The fatigue results predicted using the structural stress method correlate well with the test results.

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.

In recent decades, there has been a growing focus on improving overall vehicle efficiency and fuel economy due to growing customer awareness and more stringent environmental regulations. Effort has been placed on improving the engine efficiency and reducing the losses of the transmission and driveline. One essential component of this process is to correctly size the transmission oil pump as it is one of the main energy consumers in the powertrain. Conversely, the oil pump has a critical mission of ensuring reliable and high quality gear shift as well as supplying lubrication and cooling oil to various components in the transmission. This paper outlines a strategy to systematically understand and quantify the main requirements for sizing the oil pump to ensure adequate performance while minimizing the energy consumption of the pump. The proposed framework is a three-legged approach.

Rapid Compression Machines (RCM) offer the ability to easily change the compression ratio and the pressure/mixture composition/temperature to gather ignition delay data at various engine relevant conditions. Therefore, RCMs with optical access to the combustion chamber can provide an effective way to analyze macroscopic spray characteristics needed to understand the spray injection process and for spray model development, validation and calibration at conditions that are suitable for engines. Fuel surrogates can help control fuel parameters, develop models for spray and combustion, and perform laser diagnostics with known fluorescence characteristics. This study quantifies and evaluates the macroscopic spray characteristics of multicomponent gasoline surrogates in comparison to their gasoline counterparts, under gasoline direct injection (GDI) engine conditions.

In this work autoignition delay times of two multi-component surrogates (high and low RON) were experimentally compared with their target full blend gasoline fuels. The study was conducted in a rapid compression machine (RCM) test facility and a direct test chamber (DTC) charge preparation approach was used for mixture preparation. Experiments were carried over the temperature range of 650K-900K and at 10 bar and 20 bar compressed pressure conditions for equivalence ratios of (Φ =) 0.6-1.3. Dilution in the reactant mixture was varied from 0% to 30% CO2 (by mass), with the O2:N2 mole ratio fixed at 1:3.76. This dilution strategy emulates exhaust gas recirculation (EGR) substitution in spark ignition (SI) engines. The multicomponent surrogate captured the reactivity trends of the gasoline-air mixtures reasonably well in comparison to the single component (iso-octane) surrogate.

As engines are equipped with an increased number of control actuators to meet fuel economy targets they become more difficult to control and calibrate. The large number of control actuators encourages the investigation of physics-based control strategies to reduce calibration time and complexity. Of particular interest is spark timing control and calibration since it has a significant influence on engine efficiency, emissions, vibration and durability. Spark timing determination to achieve a desired combustion phasing is currently an empirical process that occurs during the calibration phase of engine development. This process utilizes a large number of stored surfaces and corrections to account for the wide range of operating environments and conditions that a given engine will experience. An obstacle to realizing feedforward physics-based combustion phasing control is the requirement for an accurate and fast combustion model.

An automobile door is one vital commodity which has its role in vehicle’s function, strength, safety, dynamics and aesthetic parameters. The door system comprises of individual components and sub-assemblies such as door upper, bolster, armrest, door main panel, map-pocket, handle, speaker and tweeter grille. Among them, armrest is an integral part which provides function and also takes care of some safety parameter for the customers. The basic function of an armrest is to provide ergonomic relief to occupant for resting his hand. Along with this, it also facilitates occupant safety during a side impact collision by absorbing the energy and not imparting the reactive force on occupant. Thus an armrest has evolved as a feature of passive safety. The armrest design should be stiff enough to withstand required elbow load condition with-in the acceptable deflection criteria. On the other hand, armrest has to absorb the dynamic force by deflecting proportionally to the side impact load.

Increase in the atmospheric temperature across the globe during summer, increases the heat load in the vehicle cabin, creating a huge thermal discomfort for the passengers. There are two scenarios where these adverse conditions can be a problem during the summer. Firstly, while driving the vehicle in traffic conditions and secondly, when the vehicle is parked under the sun. When the vehicle is exposed to the radiation from the sun for a period, the cabin temperature can reach alarming levels, which may have serious discomfort and health effects on the people entering the vehicle. Although there are options of remote switching on of air conditioners, they are restricted to vehicles having an automatic transmission and availability of the mobile network. So, it is important to explore the possible options which can be used for restricting the external heat load to the cabin.

Maintaining the fuel temperature and fuel system components below certain values is an important design objective. Predicting these temperatures is therefore one of the key parts of the vehicle’s thermal management process. One of the physical processes affecting fuel tank temperature is fuel vaporization, which is controlled by the vapor pressure in the tank, fuel composition and fuel temperature. Models are developed to enable the computation of the fuel temperature, fuel vaporization rate in the tank, fuel temperatures along the fuel supply lines, and follow its path to the charcoal canister and into the engine intake. For diesel fuel systems where a fuel return line is used to return excess fluid back to the fuel tank, an energy balance will be considered to calculate the heat added from the high-pressure pump and vehicle under-hood and underbody.

Component sizing generally represents a demanding and time-consuming task in the development process of electrified powertrains. A couple of processes are available in literature for sizing the hybrid electric vehicle (HEV) components. These processes employ either time-consuming global optimization techniques like dynamic programming (DP) or near-optimal techniques that require iterative and uncertain tuning of evaluation parameters like the Pontryagin’s minimum principle (PMP). Recently, a novel near-optimal technique has been devised for rapidly predicting the optimal fuel economy benchmark of design options for electrified powertrains. This method, named slope-weighted energy-based rapid control analysis (SERCA), has been demonstrated producing results comparable to DP, while limiting the associated computational time by near two orders of magnitude.

The trend to simultaneously improve fuel economy and engine performance has led to industry growth of turbocharged engines and as a result, the need to address their undesirable airborne noise attributes. This presents some unique engineering challenges as higher customer expectations for Noise Vibration Harshness (NVH), and other vehicle-level attributes increase over time. Turbocharged engines possess higher frequency noise content compared to naturally aspirated engines. Therefore, as an outcome, whoosh noise in the Air Induction System (AIS) during tip in conditions is an undesirable attribute that requires high frequency attenuation enablers. The traditional method for attenuation of this type of noise has been to use resonators which adds cost, weight and requires packaging space that is often at a premium in the under-hood environment.

To comply with the stringent fuel consumption requirements, many automobile manufacturers have launched vehicle electrification programs which are representing a paradigm shift in vehicle design. Looking specifically at powertrain calibration, optimization approaches were developed to help the decision-making process in the powertrain control. Due to computational power limitations the most common approach is still the use of powertrain calibration tables in a rule-based controller. This is true despite the fact that the most common manual tuning can be quite long and exhausting, and with the optimal consumption behavior rarely being achieved. The present work proposes a simulation tool that has the objective to automate the process of tuning a calibration table in a powertrain model. To achieve that, it is first necessary to define the optimal reference performance.

This paper presents a method to model the transmission mechanical power loss for the unloaded and loaded losses on a planetary gearset. In this analysis, the transmission losses are differentiated into losses due to fluid churning; losses due to fluid shear between the walls of rotating parts; losses due to fluid shear between motors' stator and rotor and losses due to the meshing of gearsets while transferring torque. This transmission mechanical power loss model is validated with test data that was obtained by independently testing an eVT transmission. The mechanical power loss model mentioned in this paper was constructed to accurately represent the test setup. From the correlation with the test data, it can be inferred that the transmission losses can be modeled within an error of 3% in the relevant region of output velocity for use in performance and fuel economy simulations.

Light-weight solutions for stamped steel components that exhibit the same or similar appearance properties for purposes of authentic feel and perception to customers will play a critical role as the progress towards reaching maximum fuel efficiency for large vehicles continues. This paper outlines the potential uses for laminated steel in large stamped steel bumper applications that would normally be stamped with thick sheet metal in order to meet vehicle level functional objectives. The paper presents the investigation of the one-for-one drop-in capabilities of the laminate steel material to existing stamping dies, special processing considerations while manufacturing, vehicle level performance comparisons, and class “A” coating options and process needs. Most of all, it will highlight the significant vehicle weight saving benefits and opportunities as compared to current production stamped steel bumpers.

This paper proposes a method to evaluate the sensitivity of the perceived quality of a panel interface design to variation in the measurements of fit and finish. The novelty of this approach is in the application of the concept of utility to fit and finish. The significance is in the ability to evaluate alternative designs with regard to perceived quality long before time and money are spent on their realization. In the automotive industry “fit and finish” is the term applied to the precision of the alignment of one part to another. Fit and finish gives the buyer a sense of the overall quality of the vehicle purely from an aesthetic perspective. Fit and finish is usually evaluated by the manufacturer through dimensional measurements of the gap and flushness conditions between panels.

Downsized turbocharged gasoline direct injection (TGDI) engines with high specific power and torque can enable reduced fuel consumption in passenger vehicles while maintaining or even improving on the performance of larger naturally aspirated engines. However, high specific torque levels, especially at low speeds, can lead to abnormal combustion phenomena such as knock or Low-Speed Pre-Ignition (LSPI). LSPI, in particular, can limit further downsizing due to resulting and potentially damaging mega-knock events. Herein, we characterize the impacts of lubricant and fuel composition on LSPI frequency in a TGDI engine while specifically exploring the correlation between fuel composition, particulate emissions, and LSPI events. Our research shows that: (1) oil composition has a strong impact on LSPI frequency and that LSPI frequency can be reduced through a carefully focused approach to lubricant formulation.

Two methods of assessing the similarity of a set of impact test signals have been proposed and used in the literature, which are cumulative variance-based and cross correlation-based. In this study, a normalized formulation unites these two approaches by establishing a relationship between the normalized cumulative variance metric (v), an overall similarity metric, and the normalized magnitude similarity metric (m) and shape similarity metric (s): v=1 − m · s. Each of these ranges between 0 and 1 (for the practical case of signals acquired with the same polarity), and they are independent of the physical unit of measurement. Under generally satisfied conditions, the magnitude similarity m is independent of the relative time shifts among the signals in the set; while the shape similarity s is a function of these.