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With the emergence of intelligent ground vehicles, an objective evaluation of vehicle mobility has become an even more challenging task. Vehicle mobility refers to the ability of a ground vehicle to traverse from one point to another, preferably in an optimal way. Numerous techniques exist for evaluating the mobility of vehicles on paved roads, both quantitatively and qualitatively, however, capabilities to evaluate their off-road performance remains limited. Whereas a vehicle’s off-road mobility may be significantly enhanced with intelligence, it also introduces many new variables into the decision making process that must be considered. In this paper, we present a decision analytic framework to accomplish this task. In our approach, a vehicle’s mobility is modeled using an operator’s preferences over multiple mobility attributes of concern. We also provide a method to analyze various operating scenarios including the ability to mitigate uncertainty in the vehicles inputs.

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.

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.

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.

This paper investigates the effect of the cetane number (CN) of a diesel fuel on the energy balance between a light duty (1.9L) and medium duty (4.5L) diesel engine. The two engines have a similar stroke to bore (S/B) ratio, and all other control parameters including: geometric compression ratio, cylinder number, stroke, and combustion chamber, have been kept the same, meaning that only the displacement changes between the engine platforms. Two Coordinating Research Council (CRC) diesel fuels for advanced combustion engines (FACE) were studied. The two fuels were selected to have a similar distillation profile and aromatic content, but varying CN. The effects on the energy balance of the engines were considered at two operating conditions; a “low load” condition of 1500 rev/min (RPM) and nominally 1.88 bar brake mean effective pressure (BMEP), and a “medium load” condition of 1500 RPM and 5.65 BMEP.

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.

Controlled autoignition (CAI) engines ideally operate at very lean stoichiometries to achieve low NOx emissions. But at high loads, when combustion approaches stoichiometric, they become noisy and severe engine knock develops. A possible cause is the development of amplifying pressure waves near the hot spots that inevitably occur in the autoigniting gas. This paper presents the results from numerical solutions at realistic engine conditions of the detailed chemical kinetic equations with acoustic wave propagation. Those calculations that involve hot spots must include a spatial dimension. Because of this, they are much more time-consuming than for the homogeneous case. A model system of mixtures of 0.5 H2-0.5 CO with air for equivalence ratios, ϕ, between 0.45 and 1.0 has been used at engine-like temperatures and pressures. These calculations investigate the behaviour for various values of ϕ, hot spot size and temperature elevation.

There is an increasing recognition of injector deposit (ID) formation in fuel injection equipment as direct injection spark ignition (DISI) engine technologies advance to meet increasingly stringent emission legislation and fuel economy requirements. While it is known that the phenomena of ID in DISI engines can be influenced by changes in fuel composition, including increasing usage of aliphatic alcohols and additive chemistries to enhance fuel performance, there is however still a great deal of uncertainty regarding the physical and chemical structure of these deposits, and the mechanisms of deposit formation. In this study, a mechanical cracking sample preparation technique was developed to assess the deposits across DISI injectors fuelled with gasoline and blends of 85% ethanol (E85).

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.

High-speed planar laser Mie scattering and Laser Induced Fluorescence (PLIF) were employed for the determination of Sauter Mean Diameter (SMD) distribution in non-evaporating diesel sprays. The effect of rail pressure, distillation profile, and consequent fuel viscosity on the drop size distribution developing during primary and secondary atomization was investigated. Samples of conventional crude-oil derived middle-distillate diesel and light distillate kerosene were delivered into an optically accessible mini-sac injector, using a customized high-pressure common rail diesel fuel injection system. Two optical channels were employed to capture images of elastic Mie and inelastic LIF scattering simultaneously on a high-speed video camera at 10 kHz. Results are presented for sprays obtained at maximum needle lift during the injection. These reveal that the emergent sprays exhibit axial asymmetry and vorticity.

Most modern high-pressure common rail diesel fuel injection systems employ an internal pressure equalization system in order to support needle lift, enabling precise control of the injected fuel mass. This results in the return of a fraction of the high-pressure diesel back to the fuel tank. The diesel fuel flow occurring in the injector spill passages is expected to be a cavitating flow, which is known to promote fuel ageing. The cavitation of diesel promotes nano-particle formation through induced pyrolysis and oxidation, which may result in deposits in the vehicle fuel system. A purpose-built high-pressure cavitation flow rig has been employed to investigate the stability of unadditised crude-oil derived diesel and paraffin-blend model diesel, which were subjected to continuous hydrodynamic cavitation flow across a single-hole research diesel nozzle.

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.

Due to ever-tightening CO2 regulations on passenger vehicles, it is necessary to find novel methods to improve powertrain system efficiency. These increases in efficiency should generally be cost effective so that the customer perceives that they add value. One approach for improving system efficiency has been the use of thermal energy management. For example, changing the flow of, or reusing “waste” heat from the powertrain to improve efficiency. Due to the interactions involved with thermal management, a system level approach is useful for exploring, selecting, and developing alternative solutions. It provides a structured approach to augment the right kind of synergies between subsystems and mitigate unintended consequences. However, one challenge with using these approaches early in a program is having appropriate metrics for assessing key aspects of the system behaviors.

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.