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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.

For a light duty truck, the frame is a structural system and it must go through a series of proving ground events to meet fatigue performance requirement. Nowadays, in order to meet stringent CAFE standards, auto manufacturers are seeking to keep the vehicle weight as light as possible. The weight reduction on the frame is a challenging task as it still needs to maintain the strength, safety, and durability fatigue performance. CAE fatigue simulation is widely used in frame design before the physical proving ground tests are performed. A typical frame durability fatigue analysis includes both the base metal fatigue analysis and seam weld fatigue analysis. Usually the gauges of the frame components are dictated by the seam weld fatigue performance so opportunities for weight reduction may exist in areas away from the welds. One method to reduce frame weight is to cut lightening holes in the areas that have little impact on the frame fatigue performance.

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.

A turbocharger is currently widely used to boost performance of an internal combustion engine. Generally, a turbocharger consists of a compressor which typically is driven by an exhaust turbine. The compressor will influence how the low frequency engine pulsation propagates in the intake system. The compressor will also produce broad-band flow induced sound due to the turbulence flow and high frequency narrowband tonal sound which is associated with rotating blade pressures. In this paper, a practical simulation procedure based on a computational fluid dynamics (CFD) approach is developed to predict the flow induced sound of a turbocharger compressor. In the CFD model of turbocharger compressor, the unsteady, moving wheel, detached eddy simulation (DES) approach are utilized. In this manner, both the broad-band and narrow-band flow induced sound are directly resolved in the CFD computation.

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.

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 describes a CAE fatigue life prediction technique for a tailgate on pickup truck cargo box with inertial forces and moments applied at mass center of the tailgate as input loads. The inertial forces and moments are calculated from the accelerations measured at the corners of the tailgate as the truck is being driven over a durability schedule at the test proving grounds. All the dynamic responses of the tailgate on cargo box, including any dynamic interactions at the pivot joints between the tailgate and box sides, are captured in the acquired data and also in the inertial forces and moments computed at the mass center. Correspondingly, all the dynamic responses are included in the CAE fatigue life predictions. The dynamic interactions at the pivot joints are simulated by using two identical CAE models, one with lateral translational constraint applied at the left pivot only and the other at the right pivot only.

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.

As the automotive industry is quickly changing towards electric vehicles, we can highlight the importance of aerodynamics and its critical role in reaching extended battery ranges for electric cars. With all new smooth underbodies, a lot of attention has turned into the effects of rim designs and tires brands and the management of these tire wakes with the vehicle. Tires are one of the most challenging areas for aerodynamic drag prediction due to its unsteady behavior and rubber deformation. With the simulation technologies evolving fast regarding modeling spinning tires for aerodynamics, this paper takes the prior work and data completed by the authors and investigates the impact on the flow fields and aerodynamic forces using the most recent developments of an Immerse Boundary Method (IBM). IBM allows us to mimic realistically a rotating and deformed tire using Lattice Boltzmann methods.

The charge air cooler (CAC), which is placed between the compressor and the engine intake manifold (IM), is an important component in a turbocharged engine. It is essential to capture the temperature change, the pressure drop or the acoustical wave behavior of the charge air cooler in the one-dimensional(1D) simulation model for the predictive accuracy of engine performance and intake noise. In this paper, the emphasis is on the acoustic modeling of an intake manifold and charge air cooler assembly for the low frequency engine intake order noise. In this assembly, the core of the charge air cooler is embedded in the plenum of the intake manifold. The modeling and correlation process is comprised of three steps. First, the charge air cooler core is removed from the intake manifold and put into a rectangular box matching its envelope with a single air inlet and outlet, thereby simplifying the complex shape of the manifold with the different runner components.

Typical production vehicle development includes road testing of a vehicle towing a trailer to evaluate powertrain thermal performance. In order to correlate tests with simulations, the aerodynamic effects of pulling a trailer behind a vehicle must be estimated. During real world operation a vehicle often encounters cross winds. Therefore, the effects of cross winds on the drag of a vehicle–trailer combination should be taken into account. Improving the accuracy of aerodynamic load prediction for a vehicle-trailer combination should in turn lead to improved simulations and better thermal performance. In order to best simulate conditions for real world trailer towing, a study was performed using reduced scale models of a Sport Utility Vehicle (SUV) and a Pickup Truck (PT) towing a medium size cargo trailer. The scale model vehicle and trailer combinations were tested in a full scale wind tunnel.

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.

There have been multiple studies on the effect of vehicle impact pulses on occupant responses, and studies on the previous and current US NCAP (New Car Assessment Program) vehicle pulses. This paper analyzes 35 mph (56.3 kph) front impact vehicle pulses and occupant responses in US NCAP tests conducted by the NHTSA from 2011 to 2019. Based on the occupant response analysis, a simple generic occupant restraint force-relative displacement model has been created. This generic model captures the fundamental restraint characteristics of the vehicles in the recent years, and together with the vehicle pulse, they provide several occupant response predictors. Furthermore, this paper proposes a new pulse severity metric PSD (Pulse Severity by Displacement) based on the vehicle impact data statistics, and uses the pulse severity to compare with other pulse severity definitions.

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.

Design for Six Sigma (DFSS) is an essential tool and methodology for innovation projects to improve the product design/process and performance. This paper aims to present an application of the DFSS Taguchi Method for an automotive/vehicle component. High-Pressure Vacuum Assist Die Casting (HPVADC) technology is used to make Cast Aluminum Front Shock Tower. During the vehicle life, Shock Tower transfers the road high impact loads from the shock absorber to the body structure. Proving Ground (PG) and washout loads are often used to assess part strength, durability life and robustness. The initial design was not meeting the strength requirement for abusive washout loads. The project identified eight parameters (control factors) to study and to optimize the initial design. Simulation results confirmed that all eight selected control factors affect the part design and could be used to improve the Shock Tower's strength and performance.

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.

Cast aluminum alloys are used for cylinder heads in internal combustion engines to meet low weight and high strength (lightweight) design requirements. In the combustion chamber, the alloy experiences harsh operating conditions; i.e., temperature variation, constrained thermal expansion, chemical reaction, corrosion, oxidation, and chemical deposition. Under these conditions, thermomechanical fatigue (TMF) damage arises in the form of mechanical damage, environmental (oxidation) damage, and creep damage. In the present work, several important properties that influence the TMF life of the cylinder head have been identified through TMF and finite element analysis (FEA). The results show that improving the strength at high temperatures helps improve TMF life on the exhaust side of the head. On the other hand, improving strength and ductility extend TMF life at low temperature on the intake side.

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.