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In the NVH domain, the cooling module is an important subsystem in ground vehicles. Recently, with the development of small high output turbocharged internal combustion (IC) engines, cooling module noise and vibration has become more challenging. Furthermore, with plug-in hybrid electric vehicle (PHEV), in some cases the cooling fan could be operational while the IC engine is not running. This poses a significant challenge for cabin noise enhancement. Small turbocharged IC engines typically require higher cooling capacity resulting in larger fan size designs with higher speed. Accurate prediction of the unbalance loads generated by cooling fan and loads transferred to the body are critical for the Noise Vibration and Harshness (NVH) performance of the vehicle. If the NVH risk of cooling module operation is not well quantified and addressed early in the program, attempts to find solutions in post launch stage could be very expensive and not as effective.

Idle shake is an important NVH attribute. Vehicles with good NVH characteristics are designed to perform excellent in IDLE and SHAKE conditions. Typically, tactile vibrations at idle are measured at the driver seat and steering wheel. Vibrations caused by engine excitation at idle are passed through several paths to the body structure. The dominant paths being the engine mounts and the half-shafts, either one of them or both can be a major factor influencing the perceived idle vibration in a vehicle. In the past, modeling the half-shafts accurately has been a challenge and often time has been ignored because of modeling complexity. This has led to idle CAE predictions not correlating with test data. The aim of this paper is to describe a finite element modeling method of half-shaft to predict idle vibrations levels.

Electronic Stop-Start (ESS) system automatically stops and restarts the engine to save energy, improve fuel economy and reduce emissions when the vehicle is stationary during traffic lights, traffic jams etc. The stop and start events cause unwanted vibrations at the seat track which induce discomfort to the driver and passengers in the vehicle. These events are very short duration events, usually taking less than a second. Time domain analysis can help in simulating this event but it is difficult to see modal interactions and root cause issues. Modal transient analysis also poses a limitation on defining frequency dependent stiffness and damping for multiple mounts. This leads to inaccuracy in capturing mount behavior at different frequencies. Most efficient way to simulate this event would be by frequency response analysis using modal superposition method.

There are many noise sources from the vehicle fuel system to generate noise inside a vehicle. Among them, the pressure pulsation due to the rapid opening and closing of gasoline engine injectors can cause undesirable fuel pulse noise. As the pressure pulsation propagates in the fuel supply line toward to rear end of the vehicle, the pressure energy is transferred from fuel lines to the vehicle underbody through clips and into the passenger compartment. It is crucial to attenuate the pressure pulsation inside the fuel line to reduce the fuel pulse noise. In this paper, a case study on developing an effective countermeasure to reduce the objectionable fuel pulse noise of a V8 gasoline injection system at engine idle condition is presented. First, the interior noise of a prototype vehicle was tested and the objectionable fuel pulse noise is exhibited. The problem frequency ranges of the pulse noise were identified.

In Automotive and Aerospace industries, sound package has an important role to control vehicle noise in order to improve passenger comfort and reduce environmental noise pollution. The most known approaches used to model the sound package are the Transfer Matrix Method (TMM) combined with Statistical Energy Analysis (SEA). The Transfer Matrix Method based approach is extensively used and well-validated for predicting the transmission loss and other vibro-acoustic indicators of multi-layer structures. However, to the best of our knowledge, the equivalent damping due to the multilayer has not been addressed yet in the literature, and it's a novel approach. In this paper, simplified formulations using TMM to compute the equivalent damping will be recalled, and an experimental study will be conducted to assess the add-on damping by sound package for different configurations.

In this paper we present an integrated approach which combines analysis of the effect of simultaneous variations in model input parameters on component or system temperatures. The sensitivity analysis can be conducted by varying model input parameters using specific values that may be of interest to the user. The alternative approach is to use a structured set of parameters generated in the form of a DFSS DOE matrix. The matrix represents a combination of simulation conditions which combine the control factors (CF) and noise factors. CF’s are the design parameters that the engineer can modify to achieve a robust design. Noise factors include parameters that are outside the control of the design engineer. In automotive thermal management, noise factors include changes in ambient temperature, exhaust gas temperatures or aging of exhaust system or heat shields for example.

Integration of automatic engine Stop/Start systems in “conventional” drivetrains with 12V starters is a relatively cost-effective measure to reduce fuel consumption. Therefore, automatic engine Stop/Start systems are becoming more prevalent and increasing market share of such systems is predicted. A quick, reliable and consistent engine start behavior is essential for customer acceptance of these systems. The launch of the vehicle should not be compromised by the Stop/Start system, which implies that the engine start time and transmission readiness for transmitting torque should occur within the time the driver releases the brake pedal and de-presses the accelerator pedal. Comfort and NVH aspects will continue to play an important role for customer acceptance of these systems. Hence, the engine stop and re-start behavior should be imperceptible to the driver from both a tactile and acoustic standpoint.

Automotive companies are studying to add extra value in their vehicles by enhancing powertrain sound quality. The objective is to create a brand sound that is unique and preferred by their customers since quietness is not always the most desired characteristic, especially for high-performance products. This paper describes the process of developing a brand powertrain sound for a high-performance vehicle using the DFSS methodology. Initially the customer's preferred sound was identified and analyzed. This was achieved by subjective evaluations through voice-of-customer clinics using vehicles of similar specifications. Objective data were acquired during several driving conditions. In order for the design process to be effective, it is very important to understand the relationship between subjective results and physical quantities of sound. Several sound quality metrics were calculated during the data analysis process.

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 additional complexity created by a larger number of control actuators motivates the use of physics-based control strategies to reduce calibration time and complexity. Combustion phasing, as one of the most important engine combustion metrics, has a significant influence on engine efficiency, emissions, vibration and durability. To realize physics-based engine combustion phasing control, an accurate prediction model is required. This research introduces physics-based control-oriented laminar flame speed and turbulence intensity models that can be used in a quasi-dimensional turbulent entrainment combustion model. The influence of laminar flame speed and turbulence intensity on predicted mass fraction burned (MFB) profile during combustion is analyzed.

As CAFE requirements increase, automotive OEMs are pursuing innovative methods to lightweight their Body In Whites (BIWs). Within FCA US, this lightweighting research and development activity often occurs through Decoupled Innovation projects. A Decoupled Innovation team comprised of engineers from the BIW Structures Group, in collaboration with Tier 1 supplier Magna Exteriors, sought to re-design a loadbearing component on the BIW that would offer significant weight savings when the current steel component was replaced with a carbon fiber composite. This paper describes the design, development, physical validation and partnership that resulted in a composite Rear Package Shelf Assembly solution for a high-volume production vehicle. As the CAFE requirements loom closer and closer, these innovation-driven engineering activities are imperative to the successful lightweighting of FCA US vehicles.

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.

One of the remaining challenges in the simulation of the aerodynamics of ground vehicles is the modeling of the airflows around the spinning tires and wheels of the vehicle. As in most advances in the development of simulation capabilities, it is the lack of appropriately detailed and accurate experimental data with which to correlate that holds back the advance of the technology. The flow around the wheels and tires and their interfaces with the vehicle body and the ground is a critical area for the development of automobiles and trucks, not just for aerodynamic forces and moments, and their result on fuel economy and vehicle handling and performance, but also for the airflows and pressures that affect brake cooling, engine cooling airflows, water spray management etc.

Engine mount is one of the temperature sensitive components in the vehicle under-hood. Due to increasing requirements for improved fuel economy, the under-hood thermal management has become very challenging in recent years. In order to study the effects of material thermal degradation on engine mount performance and durability; it is required to estimate the temperature of engine mount rubber during various driving conditions. The effect of temperature on physical properties of natural rubber can then be evaluated and the life of engine mount can be estimated. In this paper, a bench test is conducted where the engine mount is exposed to a step change in the environment around it, and the temperature of the rubber section is recorded at several points till a steady state temperature is reached. A time response curve is generated, from which a time constant is determined.

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.

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.

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.

The test cycle average drag coefficient is examined for the variation of allowable EPA coastdown ambient conditions. Coastdown tests are ideally performed with zero wind and at SAE standard conditions. However, often there is some variability in actual ambient weather conditions during testing, and the range of acceptable conditions is further examined in detail as it pertains to the effect on aerodynamic drag derived from the coastdown data. In order to “box” the conditions acceptable during a coastdown test, a sensitivity analysis was performed for wind averaged drag (CD¯) as well as test cycle averaged drag coefficients (CDWC) for the fuel economy test cycles. Test cycle average drag for average wind speeds up to 16 km/h and temperatures ranging from 5C to 35C, along with variation of barometric pressure and relative humidity are calculated. The significant effect of ambient cross winds on coastdown determined drag coefficient is demonstrated.

Every passing year automotive engineers are challenged to attain higher fuel economy and improved emission targets. One widely used approach is to use Cooled Exhaust Gas Recirculation (CEGR) to meet these objectives. Apart from reducing emissions and improving fuel economy, CEGR also plays a significant role in knock mitigation in spark ignited gasoline engines. Generally, CEGR is introduced into the intake manifold in SI gasoline engine. Even though the benefits of using CEGR are significant, they can be easily negated by the uneven CEGR flow distribution between the cylinders, which can result in combustion instability. This paper describes the application of co-simulation between one and three dimensional tools to accurately predict the distribution of CEGR to the cylinders and the effect of its distribution on engine performance.

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.

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.