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The Composite Lightweight Automotive Suspension System is a composite rear suspension knuckle/tieblade consisting of UD prepreg (epoxy resin), SMC (vinylester resin) carbon fibre and a steel insert to reduce the weight of the component by 35% and reduce Co2. The compression moulding manufacturing process and CAE optimisation are unique and ground-breaking for this product and are designed to allow high volume manufacture of approx. 30,000 vehicles per year. The manufacturing techniques employed allow for multi-material construction within a five minute cycle time to make the process viable for volume manufacture. The complexities of the design lie in the areas of manufacturing, CAE prediction and highly specialised design methods. It is a well-known fact that the performance of a composite part is primarily determined by the way it is manufactured.

In this paper, a soft computing approach to a model-free vehicle stability control (VSC) algorithm is presented. The objective is to create a fuzzy inference system (FIS) that is robust enough to operate in a multitude of vehicle conditions (load, tire wear, alignment), and road conditions while at the same time providing optimal vehicle stability by detecting and minimizing loss of traction. In this approach, an adaptive neuro-fuzzy inference system (ANFIS) is generated using previously collected data to train and optimize the performance of the fuzzy logic VSC algorithm. This paper outlines the FIS detection algorithm and its benefits over a model-based approach. The performance of the FIS-based VSC is evaluated via a co-simulation of MATLAB/Simulink and CarSim model of the vehicle under various road and load conditions. The results showed that the proposed algorithm is capable of accurately indicating unstable vehicle behavior for two different types of vehicles (SUV and Sedan).

This paper presents the application of a proposed fuzzy inference system as part of a stability control design scheme implemented with active steering actuator sets. The fuzzy inference system is used to detect the level of overseer/understeer at the high level and a speed-adaptive activation module determines whether an active front steering, active rear steering, or active 4 wheel steering is suited to improve vehicle handling stability. The resulting model-free system is capable of minimizing the amount of model calibration during the vehicle stability control development process as well as improving vehicle performance and stability over a wide range of vehicle and road conditions. A simulation study will be presented that evaluates the proposed scheme and compares the effectiveness of active front steer (AFS) and active rear steer (ARS) in enhancing the vehicle performance. Both time and frequency domain results are presented.

A new turbocharged 60° 2.7L 4V-V6 gasoline engine has been developed by Ford Motor Company for both pickup trucks and car applications. This engine was code named “Nano” due to its compact size; it features a 4-valves DOHC valvetrain, a CGI cylinder block, an Aluminum ladder, an integrated exhaust manifold and twin turbochargers. The goal of this engine is to deliver 120HP/L, ULEV70 emission, fuel efficiency improvements and leadership level NVH. This paper describes the upfront design and optimization process used for the NVH development of this engine. It showcases the use of analytical tools used to define the critical design features and discusses the NVH performance relative to competitive benchmarks.

In the thermal expansion valve (TXV) refrigerant system, transient high-pitched whistle around 6.18 kHz is often perceived following air-conditioning (A/C) compressor engagements when driving at higher vehicle speed or during vehicle acceleration, especially when system equipped with the high-efficiency compressor or variable displacement compressor. The objectives of this paper are to conduct the noise source identification, investigate the key factors affecting the whistle excitation, and understand the mechanism of the whistle generation. The mechanism is hypothesized that the whistle is generated from the flow/acoustic excitation of the turbulent flow past the shallow cavity, reinforced by the acoustic/structural coupling between the tube structural and the transverse acoustic modes, and then transmitted to evaporator. To verify the mechanism, the transverse acoustic mode frequency is calculated and it is coincided to the one from measurement.

A CAE method has been developed to address engine tonal noise and whine due to the excitation from a gerotor oil pump. The method involves a multidisciplinary approach including CFD, frequency-response structural analysis and acoustic analysis. The results from the application of the method applied to a couple of pumps with different designs are discussed. Engine tonal noise improvement through reduction in the excitation source from the pump and also stiffening the excitation path from the pump to the engine are studied. The effect of component modal alignment with oil pump orders is addressed as well.

Driveline plunge mechanism dynamics has a significant contribution to the driver's perceivable transient NVH error states and to the transmission shift quality. As it accounts for the pitch or roll movements of the front powerplant and rear drive unit, the plunging joints exhibit resisting force in the fore-aft direction under various driveline torque levels. This paper tackles the difficult task of quantifying the coefficient of static friction and the coefficient of dynamic friction in a simple to use metric as it performs in the vehicle. The comparison of the dynamic friction to the static friction allows for the detection of the occurrence of stick-slip in the slip mechanism; which enables for immediate determination of the performance of the design parameters such as spline geometry, mating parts fit and finish, and lubrication. It also provides a simple format to compare a variety of designs available to the automotive design engineer.

Drivelines used in modern pickup trucks commonly employ universal joints. This type of joint is responsible for second driveshaft order vibrations in the vehicle. Large displacements of the joint connecting the driveline and the rear axle have a detrimental effect on vehicle NVH. As leaf springs are critical energy absorbing elements that connect to the powertrain, they are used to restrain large axle windup angles. One of the most common types of leaf springs in use today is the multi-stage parabolic leaf spring. A simple SAE 3-link approximation is adequate for preliminary studies but it has been found to be inadequate to study axle windup. A vast body of literature exists on modeling leaf springs using nonlinear FEA and multibody simulations. However, these methods require significant amount of component level detail and measured data. As such, these techniques are not applicable for quick sensitivity studies at design conception stage.

OEMs are racing to develop lightweight vehicles as government regulations now mandate automakers to nearly double the average fuel economy of new cars and trucks by 2025. Lightweight materials such as aluminum, magnesium and carbon fiber composites are being used as structural members in vehicle body and suspension components. The reduction in weight in structural panels increases noise transmission into the passenger compartment. This poses a great challenge in vehicle sound package development since simply increasing weight in sound package components to reduce interior noise is no longer an option [1]. This paper discusses weight saving approaches to reduce noise level at the sources, noise transmission paths, and transmitted noise into the passenger compartment. Lightweight sound package materials are introduced to treat and reduce airborne noise transmission into multi-material lightweight body structure.

Lightweighting of vehicle panels enclosing vehicle cabin causes NVH degradation since engine, road, and wind noise acoustic sources propagate to the vehicle interior through these panels. In order to reduce this NVH degradation, there is a need to develop new NVH sound package materials and designs for use in lightweight vehicle design. Statistical Energy Analysis (SEA) model can be an effective CAE design tool to develop NVH sound packages for use in lightweight vehicle design. Using SEA can help engineers recover the NVH deficiency created due to sheet metal lightweighting actions. Full vehicle SEA model was developed to evaluate the high frequency NVH performance of “Vehicle A” in the frequency range from 200 Hz to 10 kHz. This correlated SEA model was used for the vehicle sound package optimization studies. Full vehicle level NVH laboratory tests for engine and tire patch noise reduction were also conducted to demonstrate the performance of sound package designs on “Vehicle A”.

Electric vehicles are receiving considerable attention because they offer a more efficient and sustainable transportation alternative compared to conventional fossil-fuel powered vehicles. Since the battery pack represents the primary energy storage component in an electric vehicle powertrain, it requires accurate monitoring and control. In order to effectively estimate the battery pack critical parameters such as the battery state of charge (SOC), state of health (SOH), and remaining capacity, a high-fidelity battery model is needed as part of a robust SOC estimation strategy. As the battery degrades, model parameters significantly change, and this model needs to account for all operating conditions throughout the battery's lifespan. For effective battery management system design, it is critical that the physical model adapts to parameter changes due to aging.

As the world's largest auto producer and consumer, China is both the most promising and complex market given the country's rapid economic growth, huge population, and many regional and segment preference differences. This research is aimed at developing data-driven demand models for customer preference analysis and prediction under a competitive market environment. Regional analysis is first used to understand the impact of geographical factors on customer preference. After a comprehensive data exploration, a customer-level mixed logit model is built to shed light on fast-growing vehicle segments in the Chinese auto market. By combining the data of vehicle purchase, consideration, and past choice, cross-shopping behaviors and brand influence are explicitly modeled in addition to the impact of customer demographics, usage behaviors, and attributes of vehicles.

Designing a vehicle body involves meeting numerous performance requirements related to different attributes such as NVH, Durability, Safety, and others. Multi-Disciplinary Optimization (MDO) is an efficient way to develop a design that optimizes vehicle performance while minimizing the weight. Since a body design evolves in course of the product development cycle, it is essential to repeat the MDO process several times as a design matures and more accurate data become available. This paper presents a real life application of the MDO process to reduce weight while optimizing performance over the design cycle of the 2015 Mustang. The paper discusses the timing and results of the applied Multi-Disciplinary Optimization process. The attributes considered during optimization include Safety, Durability and Body NVH. Several iterations of MDO have been performed at different milestones in the design cycle leading to a significant weight reduction of the already optimized design by over 16kg.

Motivated by a combination of increasing consumer demand for fuel efficient vehicles, more stringent greenhouse gas, and anticipated future Corporate Average Fuel Economy (CAFE) standards, automotive manufacturers are working to innovate in all areas of vehicle design to improve fuel efficiency. In addition to improving aerodynamics, enhancing internal combustion engines and transmission technologies, and developing alternative fuel vehicles, reducing vehicle weight by using lighter materials and/or higher strength materials has been identified as one of the strategies in future vehicle development. Weight reduction in vehicle components, subsystems and systems not only reduces the energy needed to overcome inertia forces but also triggers additional mass reduction elsewhere and enables mass reduction in full vehicle levels.

This paper presents a numerical study of trace knocking combustion of ethanol/gasoline blends in a modern, single cylinder SI engine. Results are compared to experimental data from a prior, published work [1]. The engine is modeled using GT-Power and a two-zone combustion model containing detailed kinetic models. The two zone model uses a gasoline surrogate model [2] combined with a sub-model for nitric oxide (NO) [3] to simulate end-gas autoignition. Upstream, pre-vaporized fuel injection (UFI) and direct injection (DI) are modeled and compared to characterize ethanol's low autoignition reactivity and high charge cooling effects. Three ethanol/gasoline blends are studied: E0, E20, and E50. The modeled and experimental results demonstrate some systematic differences in the spark timing for trace knock across all three fuels, but the relative trends with engine load and ethanol content are consistent. Possible reasons causing the differences are discussed.

A study and analysis of the relation of biodiesel chemical structures to the resulting soot characteristics and soot oxidative reactivity is presented. Soot samples generated from combustion of various methyl esters, alkanes, biodiesel and diesel fuels in laminar co-flow diffusion flames are analyzed to evaluate the impact of fuel-bound oxygen in fatty acid esters on soot oxidation behavior. Thermogravimetric analysis (TGA) of soot samples collected from diffusion flames show that chemical variations in biodiesel ester compounds have an impact on soot oxidative reactivity and soot characteristics in contrast to findings reported previously in the literature. Soot derived from methyl esters with shorter alkyl chains, such as methyl butyrate and methyl hexanoate, exhibit higher reactivity than those with longer carbon chain lengths, such as methyl oleate, which are more representative of biodiesel fuels.

This paper proposes an approach to determine driver's driving behavior, style or habit during vehicle handling maneuvers and heavy traction and braking events in real-time. It utilizes intelligence inferred from driver's control inputs, vehicle dynamics states, measured signals, and variables processed inside existing control modules such as those of anti-lock braking, traction control, and electronic stability control systems. The algorithm developed for the proposed approach has been experimentally validated and shows the effectiveness in characterizing driver's handling behavior. Such driver behavior can be used for personalizing vehicle electronic controls, driver assistant and active safety systems, and the other vehicle control features.

Hydrogen fueled internal combustion engines have potential for high thermal efficiencies; however, high efficiency conditions can produce high nitrogen oxide emissions (NOx) that are challenging to treat using conventional 3-way catalysts. This work presents the results of an experimental study to reduce NOx emissions while retaining high thermal efficiencies in a single-cylinder research engine fueled with hydrogen. Specifically, the effects on engine performance of the injection of water into the intake air charge were explored. The hydrogen fuel was injected into the cylinder directly. Several parameters were varied during the study, including the amount of water injected into the intake charge, the amount of fuel injected, the phasing of the fuel injection, the number of fuel injection events, and the ignition timing. The results were compared with expectations for a conventionally operated hydrogen engine where load was controlled through changes in equivalence ratio.

The Multi Material Lightweight Vehicle (MMLV), developed by Magna International and Ford Motor Company, is a result of US Department of Energy project DE-EE0005574. The project demonstrated the lightweighting potential of a five-passenger sedan while maintaining vehicle performance and occupant safety. Prototype vehicles were manufactured and limited full-vehicle testing was conducted. The Mach-I vehicle design, comprised of commercially-available materials and production processes, achieved a 364 kg (23.5%) full-vehicle mass reduction. This resulted in environmental benefits and fuel economy improvements. A significant factor in the overall MMLV mass reduction was the decrease in the powertrain system weight from 340 kg (conventional) to 267 kg (MMLV). This enabled the application of a 1.0-liter three-cylinder engine as the main powerplant. By downsizing the engine, and by implementing material changes within the engine, the weight of the dressed engine was lowered by 29 kg.

This paper details the lightweighting efforts of the Ford Research & Advanced Transmission team as part of the Multi Material Lightweight Vehicle Project. The Multi Material Lightweight Vehicle (MMLV) developed by Magna International and Ford Motor Company is a result of a US Department of Energy project DE-EE0005574. The project demonstrates the lightweighting potential of a five passenger sedan, while maintaining vehicle performance and occupant safety. Prototype vehicles were manufactured and limited full vehicle testing was conducted. The Mach-I vehicle design, comprised of commercially available materials and production processes, achieved a 364kg (23.5%) full vehicle mass reduction, enabling the application of a 1.0-liter three cylinder engine resulting in a significant environmental benefits and fuel consumption reduction.