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This paper describes the work performed in predicting and measuring the contribution of oil churning to the no-load losses of a commercial truck axle at typical running speeds. A computational fluid dynamics (CFD) analysis of the churning losses was conducted. The CFD model accounts for design geometry, operating speed, temperature, and lubricant properties. The model calculates the oil volume fraction and the torque loss caused by oil churning due to the viscous and inertia effects of the fluid. CFD predictions of power losses were then compared with no-load measurements made on a specially developed, dynamometer-driven test stand. The same axle used in the CFD model was tested in three different configurations: with axle shafts, with axle shafts removed, and with ring gear and carrier removed. This approach to testing was followed to determine the contribution of each source of loss (bearings, seals, and churning) to the total loss.

Prediction based optimal energy management systems are a topic of high interest in the automotive industry as an effective, low-cost option for improving vehicle fuel efficiency. With the continuing development of connected and autonomous vehicle (CAV) technology there are many data streams which may be leveraged by transportation stakeholders. The Suite of CAVs-derived data streams includes advanced driver-assistance (ADAS) derived information about surrounding vehicles, vehicle-to-vehicle (V2V) communications for real time and historical data, and vehicle-to-infrastructure (V2I) communications. The suite of CAVs-derived data streams have been demonstrated to enable improvements in system-level safety, emissions and fuel economy.

Recently, a new technology, termed 2-way SCR/DPF by the authors, has been developed by several catalyst suppliers for diesel exhaust emission control. Unlike a conventional emission control system consisting of an SCR catalyst followed by a catalyzed DPF, a wall-flow filter is coated with SCR catalysts for controlling both NOx and PM emissions in a single catalytic converter, thus reducing the overall system volume and cost. In this work, the potential and limitations of the Cu/Zeolite-based SCR/DPF technology for meeting future emission standards were evaluated on a pick-up truck equipped with a prototype light-duty diesel engine.

Sequel is the third vehicle in GM's Reinvention of the Automobile and is the first zero emissions passenger vehicle to drive more than 300 miles on public roads without refueling or recharging. It is purpose-built around the hydrogen storage and fuel cell systems and uses the skateboard principle introduced in the Autonomy vision concept and the Hy-wire proof-of-concept vehicles. Sequel's aluminum structure, Flexray controlled chassis-by-wire systems and AWD system comprising a single front electric motor and two rear wheel motors make it, perhaps, the most technically advanced automobile ever built. The paper describes the vehicle's design and performance characteristics.

A fully flexible valve actuation (FFVA) system was developed for a single cylinder research engine to investigate high efficiency clean combustion (HECC) in a diesel engine. The main objectives of the study were to examine the emissions, performance, and combustion characteristics of the engine using late intake valve closing (LIVC) to determine the benefits and limitations of this strategy to meet Tier 2 Bin 5 NOx requirements without after-treatment. The most significant benefit of LIVC is a reduction in particulates due to the longer ignition delay time and a subsequent reduction in local fuel rich combustion zones. More than a 95% reduction in particulates was observed at some operating conditions. Combustion noise was also reduced at low and medium loads due to slower heat release. Although it is difficult to assess the fuel economy benefits of LIVC using a single cylinder engine, LIVC shows the potential to improve the fuel economy through several approaches.

With increasingly stringent emissions regulations and concurrent requirements for enhanced engine thermal efficiency, a comprehensive characterization of the automotive gasoline fuel spray has become essential. The acquisition of accurate and repeatable spray data is even more critical when a combustion strategy such as gasoline direct injection is to be utilized. Without industry-wide standardization of testing procedures, large variablilities have been experienced in attempts to verify the claimed spray performance values for the Sauter mean diameter, Dv90, tip penetration and cone angle of many types of fuel sprays. A new SAE Recommended Practice document, J2715, has been developed by the SAE Gasoline Fuel Injection Standards Committee (GFISC) and is now available for the measurement and characterization of the fuel sprays from both gasoline direct injection and port fuel injection injectors.

While machine learning in autonomous vehicles development has increased significantly in the past few years, the use of reinforcement learning (RL) methods has only recently been applied. Convolutional Neural Networks (CNNs) became common for their powerful object detection and identification and even provided end-to-end control of an autonomous vehicle. However, one of the requirements of a CNN is a large amount of labeled data to inform and train the neural network. While data is becoming more accessible, these networks are still sensitive to the format and collection environment which makes the use of others’ data more difficult. In contrast, RL develops solutions in a simulation environment through trial and error without labeled data. Our research expands upon previous research in RL and Proximal Policy Optimization (PPO) and the application of these algorithms to 1/18th scale cars by expanding the application of this control strategy to a full-sized passenger vehicle.

Global environmental and economic concerns regarding increasing fuel consumption and greenhouse gas emission are driving changes to legislative regulations and consumer demand. As regulations become more stringent, advanced engine technologies must be developed and implemented to realize desired benefits. Discrete variable valve lift technology is a targeted means to achieve improved fuel economy in gasoline engines. By limiting intake air flow with an engine valve, as opposed to standard throttling, road-load pumping losses are reduced resulting in improved fuel economy. This paper focuses on the design and development of a switching roller finger follower system which enables two mode discrete variable valve lift on end pivot roller finger follower valvetrains. The system configuration presented includes a four-cylinder passenger car engine with an electro-hydraulic oil control valve, dual feed hydraulic lash adjuster, and switching roller finger follower.

Prediction of vehicle velocity is important since it can realize improvements in the fuel economy/energy efficiency, drivability, and safety. Velocity prediction has been addressed in many publications. Several references considered deterministic and stochastic approaches such as Markov chain, autoregressive models, and artificial neural networks. There are numerous new sensor and signal technologies like vehicle-to-vehicle and vehicle-to-infrastructure communication that can be used to obtain inclusive datasets. Using these inclusive datasets of sensors in deep neural networks, high accuracy velocity predictions can be achieved. This research builds upon previous findings that Long Short-Term Memory (LSTM) deep neural networks provide low error velocity prediction. We developed an LSTM deep neural network that uses different groups of datasets collected in Fort Collins, Colorado.

General Motors' 3.6L DOHC 4V V6 engine has been upgraded to provide substantial improvements in performance, fuel economy, and emissions for the 2008 model year Cadillac CTS and STS. The fundamental change was a switch from traditional manifold-port fuel injection (MPFI) to spark ignition direct injection (SIDI). Additional modifications include enhanced cylinder head and intake manifold air flow capacities, optimized camshaft profiles, and increased compression ratio. The SIDI fuel system presented the greatest opportunities for system development and optimization in order to maximize improvements in performance, fuel economy, and emissions. In particular, the injector flow rate, orifice geometry, and spray pattern were selected to provide the optimum balance of high power and torque, low fuel consumption, stable combustion, low smoke emissions, and robust tolerance to injector plugging.

This paper presents four methodologies for modeling gear mesh excitations in simple and compound planetary gear sets. The gear mesh excitations use simplified representations of the gear mesh contact phenomenon so that they can be implemented in a numerically efficient manner. This allows the gear mesh excitations to be included in transmission system-level, multibody dynamic models for the assessment of operating noise and vibration levels. After presenting the four approaches, a description is made regarding how they have been implemented in software. Finally, example models are used to do a comparison between the methods

The dash mat is one of the most important acoustic components in the vehicle for both powertrain noise and road noise attenuation. To optimize acoustic performance and mass requirements in the advanced development stage, analytical modeling is essential. The development of a detailed Statistical Energy Analysis (SEA) model of a dash mat is discussed in this paper. Modeling techniques and correlation with test are presented for two different production dash mat designs, a barrier-decoupler conventional system and a dual layer dissipative system without a mass barrier. The material properties and thickness distribution are used in the SEA model together with the geometry information of the dash panel. With the SEA model suitably correlated, trade-off studies are conducted to investigate the relationship between mass reduction of the barrier and change in decoupler thickness. The effects of air gaps are also considered in both modeling and testing.

The work presented in this paper outlines the design and development of a compliant sprocket for balancer drives in an effort to reduce the noise levels related to chain-sprocket meshing. An experimental observation of a severe chain noise around a resonant engine speed with the Dual-Mass Flywheel (DMF) and standard build solid (fixed) balancer drive sprocket. Torsional oscillation at the crankshaft nose at full load is induced by uneven running of crankshaft with a dual-mass flywheel system. This results in an increase of the undesirable impact noise caused by the meshing between the chain-links and the engagement/disengagement regions of sprockets, and the clatter noise from the interaction between the vibrating chain and the guides. This paper evaluates and discusses the benefits that the compliant sprocket design provided. A multi-body dynamics system (MBS) model of the balancer chain drive has been developed, validated, and used to investigate the chain noise.

A numerical investigation of automobile sunroof buffeting on a prototype sport utility vehicle (SUV) is presented, including experimental validation. Buffeting is an unpleasant low frequency booming caused by flow-excited Helmholtz resonance of the interior cabin. Accurate prediction of this phenomenon requires accounting for the bi-directional coupling between the transient shear layer aerodynamics (vortex shedding) and the acoustic response of the cabin. Numerical simulations were performed using the PowerFLOW code, a CFD/CAA software package from Exa Corporation based on the Lattice Boltzmann Method (LBM). The well established LBM approach provides the time-dependent solution to the compressible Navier-Stokes equations, and directly captures both turbulent and acoustic pressure fluctuations over a wide range of scales given adequate computational grid resolution.

This work provides an effective engineering method of building a part-load engine simulation model from a wide-open throttle (WOT) engine model and available dynamometer data. It shows how to perform part-load engine simulation using optimizer for targeted manifold absolute air pressure (MAP) on a basic matrix of engine speed and MAP. Key combustion parameters were estimated to cover the entire part-load region based on affordable assumptions and limitations. Engine rubbing friction and pumping friction were combined to compare against the motoring torque. The emission data from GM dynamometer laboratory were used to compare against engine simulation results after attaching the RLT sensor to record emission data in the engine simulation model.

Fully flexible valve actuation (FFVA) system, often referred to as camless valvetrain, employs electronically controlled actuators to drive the intake and/or exhaust valves. This technology enables the engine controller to tailor the valve event according to the engine operating condition in real-time to improve fuel economy, emissions and performance. At GM Research and Development Center, we have developed laboratory electro-hydraulic FFVA systems for single cylinder gasoline engines. The objective of this work is to develop a FFVA system for advanced diesel combustion research. There are three major differences between gasoline and diesel engines in terms of applying the FFVA systems. First, the orientation of the diesel engine valves and the location of the fuel injection system complicate the packaging issue. Second, the clearance between the valves and the piston for diesel engines are extremely small.

This paper presents an innovative automobile application of Computational Fluid Dynamics (CFD) as a complement to wind tunnel experimentation for the evaluation of rain water and wiper wash flow on the exterior of a moving vehicle. In addition to calculating the air flow around a car, a multi-phase CFD code was used to simulate rain drops in the air stream, rain drops impinging on the vehicle, and the transport of the “thin liquid film” of water on the vehicle surfaces. Time-dependent results for the location, velocity, and height of the water film on the windshield, A-pillar, and side glass were obtained. The CFD results compared favorably with a wind tunnel procedure. The variation of the calculated water film corresponded with observed patterns of water streaks on test vehicles. Design iterations performed on the computational model also agreed with similar test configurations.

The new regulations to reduce emissions have resulted in the development of new techniques to maintain or enhance competitive performance. A requirement for the manifold is to help meet the reduction in cold start emissions, particularly during the transient conditions from start to 100 seconds following the Federal Test Procedures for vehicle emissions. Finite element computer models were developed to predict inner and outer wall temperatures, and to determine structural soundness. Tests were performed to assure that noise levels were minimized. Dynamometer lab and field tests were performed to verify that the manifold would meet the design requirements. From the results of these tests and analyses, modifications were made to the weld and manufacturing techniques to improve product life and reduce noise. Dual wall manifolds have proven durability to meet high exhaust gas temperatures up to 1650°F (900°C), while meeting the performance, noise, and weight reduction goals.

Homogeneous Charge Compression Ignition (HCCI) is a combustion concept which has the potential for efficiency comparable to a DI Diesel engine with low NOx and soot emissions. However, HCCI is difficult to control, especially at low speeds and loads. One way to assist with combustion control and to extend operation to low speed and loads is to close the exhaust valve before TDC of the exhaust stroke, trapping and recompressing some of the hot residual. Further advantages can be attained by injecting the fuel into this trapped, recompressed mixture, where chemical reactions occur that improve ignitability of the subsequent combustion cycle. Even further improvement in the subsequent combustion cycle can be achieved by applying a spark, leading to a spark-assisted HCCI combustion concept.

Light weight quiet small internal combustion engines that meet cost and required reliability parameters are important in the consumer product market as well as in the industrial environment. In the design of these lightweight powerplants, accurate analysis of factors which influence immediate and long-term effects is essential. Hologram interferometry is used to provide a full field view of engine cylinder wall deformations which may lead to noise, fatigue and related inefficiencies. The technique allows for the evaluation of cylinder deformation caused by thermal and mechanical loads. Static loads are applied to predict the deformation of the engine at specific points in the operating cycle.