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A simulation framework with a validated system model capable of estimating fuel consumption is a valuable tool in analysis and design of the hybrid vehicles. In particular, the framework can be used for (1) benchmarking the fuel economy achievable from alternate hybrid powertrain technologies, (2) investigating sensitivity of fuel savings with respect to design parameters (for example, component sizing), and (3) evaluating the performance of various supervisory control algorithms for energy management. Presenter Chinmaya Patil, Eaton Corporation

The current simulation models of EV and ICE Vehicles are well known in industry for their use in estimating the fuel economy or Range benefits because of controller calibrations and component sizing. However, there is a gap in understanding the behavior of accessories such as HVAC, power steering and other such auxiliary loads and the energy losses associated with them. Impact of thermal behavior of electronics on vehicle range also needs to be studied in detail. These kinds of studies help OEM and tier 1 manufactures in improving their design concepts significantly with minimum cost and development time. Hence, the focus of this study is on building simulation models of thermal, electrical, traction and control circuits of a typical electric vehicle. These models are then integrated, and analysis is performed to understand vehicle system level performance metrics.

Diesel Cylinder Deactivation (CDA) has been shown in previous work to increase exhaust temperatures, improve fuel efficiency, and reduce engine-out NOx for engine loads up to 3 bar BMEP. The purpose of this study is to determine whether or not the turbocharger needs to be altered when implementing CDA on a diesel engine. This study investigates the effect of CDA on exhaust temperature, fuel efficiency, and turbocharger performance in a 15L heavy-duty diesel engine under low-load (0-3 bar BMEP) steady-state operating conditions. Two calibration strategies were evaluated. First, a “stay-hot” thermal management strategy in which CDA was used to increase exhaust temperature and reduce fuel consumption. Next, a “get-hot” strategy where CDA and elevated idle speed was used to increase exhaust temperature and exhaust enthalpy for rapid aftertreatment warm-up.

The paper covers the NOx performance evaluation of an LNT + SCR system designed to meet the 2010 on-highway heavy-duty (HD) US EPA emission standards. The system combines a fuel reformer catalyst (REF), lean NOx trap (LNT), diesel particulate filter (DPF), and selective catalytic reduction (SCR) in series, to reduce engine-out NOx and PM. System NOx reduction performance was verified in an engine dynamometer test cell, using a 2007 7.6L medium-duty engine. System NOx performance was characterized using fresh LNT and SCR along with hydrothermal aged LNT and fresh SCR. Test results show levels consistent with EPA 2010 limits under various test conditions. Catalysts performance was characterized at eight steady engine-operating conditions (A100, B50, B75, A75, B100, C100, C75, C50, across a 13-mode Supplemental Emission Test (SET), and an on-highway Heavy Duty Federal Test Procedure (HD-FTP).

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.

ADVISOR is a flexible drivetrain analysis tool, developed in MATLAB/Simulink® to compare fuel economy and emissions performance between different drivetrain configurations. This paper reports a couple of numerical issues with application of ADVISOR 2002 to commercial vehicles with traditional powertrain systems. One instance is when ADVISOR model is set up to simulate running a heavy-duty (HD) truck with an automated manual transmission (AMT) on a demanding pickup-delivery duty cycle. The other is highlighted during an analysis of a medium-duty (MD) truck with an automatic transmission (AT) where wide-open throttle, i.e., fast acceleration is requested. These two cases have shown different numerical difficulties by using ADVISOR 2002. Based on studying the details of the models, solutions to these numerical issues are developed. The simulation results will demonstrate the effectiveness of these solutions.

The Mississippi State University Formula SAE race car upright was optimized using radial basis function metamodels and an internal state variable (ISV) plasticity damage material model. The weight reduction of the upright was part of a goal to reduce the weight of the vehicle by 25 percent. Using an optimization routine provided an upright design that is lighter that helps to improve vehicle fuel economy, acceleration, and handling. Finite element (FE) models of the upright were produced using quadratic tetrahedral elements. Using tetrahedral elements provided a quick way to produce the multiple FE models of the upright required for the multi-objective optimization. A design of experiments was used to determine how many simulations were required for the optimization. The loads for the simulations included braking, acceleration, and corning loads seen by the car under track conditions.

This paper discusses the effect of torque vectoring differential on improving vehicle handling and stability performance. The torque vectoring concept has been analyzed. The vehicle discussed in this paper is an AWD vehicle with torque vectoring differential in the rear and a torque biasing center differential. First, simulation results with vehicle model in CarSim® and torque vectoring control algorithm in Matlab®/Simulink® is discussed. Then, experimental results for vehicle tested at winter and summer test facility is presented. Both simulation and experimental results demonstrate the effectiveness of torque vectoring differential on vehicle handling & stability.

On-board measurements of fuel consumption and vehicle exhaust emissions of NOx, HC, CO, CO2, and PM are being conducted for three types of commercially available city buses in Guangzhou, China. The selected vehicles for this test include a diesel bus with Eaton hybrid electric powertrain, a conventional diesel bus with automated mechanical transmission (AMT), and a LPG powered city bus with manual transmission (MT). All of the tested vehicles were instrumented with on-board measurements. Horiba OBS-2200 was used for measuring NOx, HC, and CO emissions; ELPI (Electrical Low Pressure Impactor) was used for PM measurement. The vehicles were tested at Hainan National Proving Ground in southern China. Test data of fuel consumption and exhaust emissions were analyzed. The city bus with Eaton hybrid electric powertrain demonstrated more than 27% fuel consumption reduction over the conventional diesel powered bus, and over 68% over the LPG bus.

This paper addresses Hardware-In-the-Loop modeling and simulation for Diesel aftertreatment controls system development. Lean NOx Trap (LNT) based aftertreatment system is an efficient way to reduce NOx emission from diesel engines. From control system perspective, the main challenge in aftertreatment system is to predict temperature at various locations and estimate the stored NOx in LNT. Accurate estimation of temperatures and NOx stored in the LNT will result in an efficient system control with less fuel penalty while still maintaining the emission requirements. The optimization of the controls will prolong the lifespan of the system by avoiding overheating the catalysts, and slow the progressive process of component aging. Under real world conditions, it is quite difficult and costly to test the performance of a such complex controller by using only vehicle tests and engine cells.

The power management control system development and vehicle test results for a medium-duty hybrid electric truck are reported in this paper. The design procedure adopted is a model-based approach, and is based on the dynamic programming technique. A vehicle model is first developed, and the optimal control actions to maximize fuel economy are then obtained by the dynamic programming method. A near-optimal control strategy is subsequently extracted and implemented using a rapid-prototyping control development system, which provides a convenient environment to adjust the control algorithms and accommodate various I/O configurations. Dynamometer-testing results confirm that the proposed algorithm helps the prototype hybrid truck to achieve a 45% fuel economy improvement on the benchmark (non-hybrid) vehicle. It also compares favorably to a conventional rule-based control method, which only achieves a 31% fuel economy improvement on the same hybrid vehicle.

This paper presents a new composite drive cycle used to evaluate and test the performance of Class 4-6 heavy-duty hybrid electric vehicles (HEVs). The new cycle is being used in the ongoing Advanced Heavy Hybrid Propulsion Systems (AHHPS) Program, sponsored by the U.S. Department of Energy. The goal was to select a cycle that is acceptable to all involved parties, has an achievable speed-time trace for target applications, represents the typical driving pattern of these applications, and is practical for testing and state-of-charge correction. These criteria were applied to numerous element and composite cycles. Ultimately, a new composite cycle was developed and selected-the Combined International Local and Commuter Cycle (CILCC). Various activities conducted under the AHHPS Program are based on this cycle, including energy auditing, modeling and simulation, system optimization, and vehicle testing.

A special vehicle dynamometer has been developed that allows engineers to evaluate driveline components and control algorithms for advanced, electrically-assisted drive systems on commercial vehicles. This dynamometer allows objective measurements of performance, fuel economy, and exhaust emissions, while the full vehicle is operated over a specified driving cycle. This system can be used to exercise the electric motor, engine, transmission and battery systems on Medium Duty Hybrid Trucks - in regeneration as well as power mode - all indoors and in a controlled, repeatable environment. This paper will provide descriptions of the operating goals, control features, and results of testing with this dynamometer. Once the various parameters have been optimized for fuel and emissions performance in this facility, the vehicle can be evaluated where it counts - on the road.

Using FEM (Finite Element Method) and other analytical approaches, a systematic methodology was developed to predict an engine valve's fatigue life. In this study, a steel (SAE 21-2N) exhaust valve on an engine with a type 2 valve train configuration was used as a test case. Temperature and stress/strain responses of each major event phase of the engine cycle were analytically simulated. CFD models were developed to simulate the exhaust gas flow to generate boundary conditions for a thermal model of the valve. FEM simulations accounted for thermal loads, temperature dependent material properties, thermal stresses, closing impact stresses and combustion load stresses. An estimated fatigue life was calculated using Miner's rule of damage accumulation in conjunction with the Modified Goodman approach for fluctuating stresses. Predicted life results correlated very well with empirical tests.

A spectral-based substructuring approach applying linear frequency response functions (FRF) is proposed for improving the accuracy of simulating the dynamics of coupled systems. The method also applies a least square singular value decomposition (SVD) scheme to overcome the inherent computational deficiency in the basic substructuring formulation. The computational problem is caused by the magnification of measurement errors during any one of the matrix inversion calculations required for this method. The primary objective of applying this approach is to examine the possibility of analyzing higher frequency response that is normally not possible using conventional modeling technique such as the direct finite and boundary element, and lumped parameter techniques. In this study, additional concepts are also evaluated to quantify the limitations and range of applicability of the proposed substructuring approach for simulating the vibration response of complex powertrain structures.

Increased demands for reduction of fuel consumption and CO2 emissions are driven by the global warming. To meet these challenges with respect to the passenger car segment the strategy of utilizing IC-engine downsizing has shown to be effective. In order to additionally meet requirements for high power and torque output supercharging is required. This can be realized using e.g. turbo-chargers, roots blowers or a combination of several such devices for the highest specific power segment. Both turbo-chargers and roots blowers can be strong sources of sound depending on the operating conditions and extensive NVH abatements such as resonators and encapsulation might be required to achieve superior vehicle NVH. For an efficient resonator tuning process in-duct acoustic source data is required. No published studies exists that describe how the gas exchange process for roots blowers can be described by acoustic sources in the frequency domain.

A simulation framework with a validated system model capable of estimating fuel consumption is a valuable tool in analysis and design of the hybrid vehicles. In particular, the framework can be used for (1) benchmarking the fuel economy achievable from alternate hybrid powertrain technologies, (2) investigating sensitivity of fuel savings with respect to design parameters (for example, component sizing), and (3) evaluating the performance of various supervisory control algorithms for energy management. This paper describes such a simulation framework that can be used to predict fuel economy of series hydraulic hybrid vehicle for any specified driver demand schedule (drive cycle), developed in MATLAB/Simulink. The key components of the series hydraulic hybrid vehicle are modeled using a combination of first principles and empirical data. A simplified driver model is included to follow the specified drive cycle.

The demand for improving fuel economy in passenger cars is continuously increasing. Eliminating energy losses within the engine is one method of achieving fuel economy improvement. Frictional energy losses account for a noticeable portion of the overall efficiency of an engine. Valvetrain friction, specifically at the camshaft interface, is one area where potential for friction reduction is evident. Several factors can impact the friction at the camshaft interface. Some examples include: camshaft lobe profile, rocker arm interface geometry, valve spring properties, material properties, oil temperature, and oil pressure. This paper discusses the results of a series of tests that experimented the changes in friction that take place as these factors are altered. The impact of varying testing conditions such as oil pressure and oil temperature was evaluated throughout the duration of the testing and described herein.

Variable valve actuation is a focus to improve fuel efficiency for passenger car engines. Various means to implement early and late intake valve closing (E/LIVC) at lower load operating conditions is investigated. The study uses GT Power to simulate on E/LIVC on a 2.5 L gasoline engine, in-line four cylinder, four valve per cylinder engine to evaluate different ways to achieve Atkinson cycle performance. EIVC and LIVC are proven methods to reduce the compression-to-expansion ratio of the engine at part load and medium load operation. Among the LIVC strategies, two non-traditional intake valve lift profiles are investigated to understand their impact on reduction of fuel consumption at low engine loads. Both the non-traditional lift profiles retain the same maximum lift as a normal intake valve profile (Otto-cycle) unlike a traditional LIVC profile (Atkinson cycle) which needs higher maximum lift.

The effects of downspeeding and supercharging a passenger car diesel engine were studied through laboratory investigation and vehicle simulation. Changes in the engine operating range, transmission gearing, and shift schedule resulted in improved fuel consumption relative to the baseline turbocharged vehicle while maintaining performance and drivability metrics. A shift schedule optimization technique resulted in fuel economy gains of up to 12% along with a corresponding reduction in transmission shift frequency of up to 55% relative to the baseline turbocharged configuration. First gear acceleration, top gear passing, and 0-60 mph acceleration of the baseline turbocharged vehicle were retained for the downsped supercharged configuration.