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The focus of this paper is on developing, modeling and simulation framework for a bias free comparison of different engine concepts in a conventional and hybrid configuration. The first unique contribution of this paper is in the development of a shift logic algorithm that allows tailoring the shift schedule to unique engine characteristics in a consistent manner. The shift schedule is intentionally generated in a generic manner by using identical set of rules for all engines. Therefore, the methodology allows a fair comparison of different engine concepts, while taking into account the individual features of the engine i.e. speed range, efficiency and maximum performance. The latter establishes a baseline for the subsequent study of hybrid configurations. The second unique contribution is the hybrid strategy optimization algorithm, also tailored to a particular engine configuration.

This work presents the development, validation and use of a SIMULINK integrated vehicle system simulation composed of engine, driveline and vehicle dynamics modules. The engine model links the appropriate number of single-cylinder modules, featuring thermodynamic models of the in-cylinder processes with transient capabilities to ensure high fidelity predictions. A detailed fuel injection control module is also included. The engine is coupled to the driveline, which consists of the torque converter, transmission, differential and prop shaft and drive shafts. An enhanced version of the point mass model is used to account for vehicle dynamics in the longitudinal and heave directions. A vehicle speed controller replaces the operator and allows the feed-forward simulation to follow a prescribed vehicle speed schedule.

The number of control actuators available on spark-ignition engines is rapidly increasing to meet demand for improved fuel economy and reduced exhaust emissions. The added complexity greatly complicates control strategy development because there can be a wide range of potential actuator settings at each engine operating condition, and map-based actuator calibration becomes challenging as the number of control degrees of freedom expand significantly. Many engine actuators, such as variable valve actuation and flow control valves, directly influence in-cylinder combustion through changes in gas exchange, mixture preparation, and charge motion. The addition of these types of actuators makes it difficult to predict the influences of individual actuator positioning on in-cylinder combustion without substantial experimental complexity.

A comprehensive quasi-dimensional computer simulation of the spark-ignition (SI) engine was used to explore part-load, fuel economy benefits of the Variable Stroke Engine (VSE) compared to the conventional throttled engine. First it was shown that varying stroke can replace conventional throttling to control engine load, without changing the engine characteristics. Subsequently, the effects of varying stroke on turbulence, burn rate, heat transfer, and pumping and friction losses were revealed. Finally these relationships were used to explain the behavior of the VSE as stroke is reduced. Under part load operation, it was shown that the VSE concept can improve brake specific fuel consumption by 18% to 21% for speeds ranging from 1500 to 3000 rpm. Further, at part load, NOx was reduced by up to 33%. Overall, this study provides insight into changes in processes within and outside the combustion chamber that cause the benefits and limitations of the VSE concept.

The development and use of a simulation of an Integrated Starter Alternator (ISA) for a High Mobility Multi-purpose Wheeled Vehicle (HMMWV) is presented here. While the primary purpose of an ISA is to provide electric power for additional accessories, it can also be utilized for mild hybridization of the powertrain. In order to explore ISA's potential for improving HMMWV's fuel economy, an ISA model capable of both producing and absorbing mechanical power has been developed in Simulink. Based on the driver's power request and the State of Charge of the battery (SOC), the power management algorithm determines whether the ISA should contribute power to, or absorb power from the crankshaft. The system is also capable of capturing some of the braking energy and using it to charge the battery. The ISA model and the power management algorithm have been integrated in the Vehicle-Engine SIMulation (VESIM), a SIMULINK-based vehicle model previously developed at the University of Michigan.

This paper is on the development process of a hydraulic hybrid passenger vehicle. A subcompact passenger vehicle is chosen for modification into a series hydraulic hybrid with the aim of achieving a fuel economy of 100 MPG (2.35 L/100km) on the Urban Dynamometer Driving Schedule (UDDS). This work develops a methodology for simultaneously designing a powertrain and power management strategy of a series hydraulic hybrid. The design process was initiated by developing a system level model validated using engine and hydraulic pump/motor testing by the US EPA at the National Vehicle and Fuel Efficiency Laboratory (NVFEL). Parametric studies were performed in order to determine the size of the pump/motors and accumulators. Several candidate engines were tested and the system models were used to determine which one could provide the best fuel economy while meeting performance constraints.

A supervisory controller strategy for a hybrid vehicle coordinates the operation of the two power sources onboard of a vehicle to maximize objectives like fuel economy. In the past, various control strategies have been developed using heuristics as well as optimal control theory. The Stochastic Dynamic Programming (SDP) has been previously applied to determine implementable optimal control policies for discrete time dynamic systems whose states evolve according to given transition probabilities. However, the approach is constrained by the curse of dimensionality, i.e. an exponential increase in computational effort with increase in system state space, faced by dynamic programming based algorithms. This paper proposes a novel approach capable of overcoming the curse of dimensionality and solving policy optimization for a system with very large design state space.

Impact of driving patterns on fuel economy is significant in hybrid electric vehicles (HEVs). Driving patterns affect propulsion and braking power requirement of vehicles, and they play an essential role in HEV design and control optimization. Driving pattern conscious adaptive strategy can lead to further fuel economy improvement under real-world driving. This paper proposes a real-time driving pattern recognition algorithm for supervisory control under real-world conditions. The proposed algorithm uses reference real-world driving patterns parameterized from a set of representative driving cycles. The reference cycle set consists of five synthetic representative cycles following the real-world driving distance distribution in the US Midwestern region. Then, statistical approaches are used to develop pattern recognition algorithm. Driving patterns are characterized with four parameters evaluated from the driving cycle velocity profiles.

A quasi-dimensional computer simulation of the turbocharged spark-ignition engine has been developed in order to study system performance as various design parameters and operating conditions are varied. The simulation is of the “filling and emptying” type. Quasi-steady flow models of the compressor, intercooler, manifolds, turbine, wastegate, and ducting are coupled with a multi-cylinder engine model where each cylinder undergoes the same thermodynamic cycle. A turbulent entrainment model of the combustion process is used, thus allowing for studies of the effects of various combustion chamber shapes and turbulence parameters on cylinder pressure, temperature, NOx emissions and overall engine performance. Valve open areas are determined either based on user supplied valve lift data or using polydyne-generated cam profiles which allow for variable valve timing studies.

Thermal barrier coatings with low conductivity and low heat capacity have been shown to improve the performance of homogeneous charge compression ignition (HCCI) engines. These coatings improve the combustion process by reducing heat transfer during the hot portion of the engine cycle without the penalty thicker coatings typically have on volumetric efficiency. Computational fluid dynamic simulations with conjugate heat transfer between the in-cylinder fluid and solid piston of a single cylinder HCCI engine with exhaust valve rebreathing are carried out to further understand the impacts of these coatings on the combustion process. For the HCCI engine studied with exhaust valve rebreathing, it is shown that simulations needed to be run for multiple engine cycles for the results to converge given how sensitive the rebreathing process is to the residual gas state.

A series hydraulic hybrid concept (SHHV) has been explored as a potential pathway to an ultra-efficient city vehicle. Intended markets would be congested metropolitan areas, particularly in developing countries. The target fuel economy was ~100 mpg or 2.4 l/100km in city driving. Such an ambitious target requires multiple measures, i.e. low mass, favorable aerodynamics and ultra-efficient powertrain. The series hydraulic hybrid powertrain has been designed and analyzed for the selected light and aerodynamic platform with the expectation that (i) series configuration will maximize opportunities for regeneration and optimization of engine operation, (ii) inherent high power density of hydraulic propulsion and storage components will yield small, low-cost components, and (iii) high efficiency and high power limits for accumulator charging/discharging will enable very effective regeneration.

An integrated vehicle system simulation has been developed to take advantage of advances in physical process and component models, flexibility of graphical programming environments (such as MATLAB-SIMULINK), and ever increasing capabilities of engineering workstations. A comprehensive, transient model of the multi-cylinder engine is linked with models of the torque converter, transmission, transfer case and differentials. The engine model is based on linking the appropriate number of single-cylinder modules, with the latter being thermodynamic models of the in-cylinder processes with built-in physical sub-models and transient capabilities to ensure high fidelity predictions. Either point mass or multi-body vehicle dynamics models can be coupled with the powertrain module to produce the ground vehicle simulation.

A hybrid electric vehicle simulation tool (HE-VESIM) has been developed at the Automotive Research Center of the University of Michigan to study the fuel economy potential of hybrid military/civilian trucks. In this paper, the fundamental architecture of the feed-forward parallel hybrid-electric vehicle system is described, together with dynamic equations and basic features of sub-system modules. Two vehicle-level power management control algorithms are assessed, a rule-based algorithm, which mainly explores engine efficiency in an intuitive manner, and a dynamic-programming optimization algorithm. Simulation results over the urban driving cycle demonstrate the potential of the selected hybrid system to significantly improve vehicle fuel economy, the improvement being greater when the dynamic-programming power management algorithm is applied.

A naturally-aspirated, Miller cycle, Spark-Ignition (SI) engine that controls output with variable intake valve closure is compared to a conventionally-throttled engine using computer simulation. Based on First and Second Law analyses, the two load control strategies are compared in detail through one thermodynamic cycle at light load conditions and over a wide range of loads at 2000 rpm. The Miller Cycle engine can use late intake valve closure (LIVC) to control indicated output down to 35% of the maximum, but requires supplemental throttling at lighter loads. The First Law analysis shows that the Miller cycle increases indicated thermal efficiency at light loads by as much as 6.3%, primarily due to reductions in pumping and compression work while heat transfer losses are comparable.

Opposed-piston 2-stroke (OP-2S) engines have the potential to achieve higher thermal efficiency than a typical diesel engine. However, the uniflow scavenging process is difficult to control over a wide range of speeds and loads. Scavenging performance is highly sensitive to pressure dynamics, port timings, and port design. This study proposes an analysis of the effects of port vane angle on the scavenging performance of an opposed-piston 2-stroke engine via simulation. A CFD model of a three-cylinder opposed-piston 2-stroke was developed and validated against experimental data collected by Achates Power Inc. One of the three cylinders was then isolated in a new model and simulated using cycle-averaged and cylinder-averaged initial/boundary conditions. This isolated cylinder model was used to efficiently sweep port angles from 12 degrees to 29 degrees at different pressure ratios.

Variable geometry turbines (VGT) are of particular interest to advanced diesel powertrains for future conventional trucks, since they can dramatically improve system transient response to sudden changes in speed and load, characteristic of automotive applications. VGT systems are also viewed as the key enabler for the application of the EGR system for reduction of heavy-duty diesel emissions. This paper applies an artificial neural network methodology to VGT modeling in order to enable representation of the VGT characteristics for any blade (nozzle) position. Following validation of the ANN model of the baseline, fixed geometry turbine, the VGT model is integrated with the diesel engine system. The latter is linked to the driveline and the vehicle dynamics module to form a complete, high-fidelity vehicle simulation.

The thermal conditions of an engine structure, in particular the wall temperatures, have been shown to have a great effect on the HCCI engine combustion timing and burn rates through wall heat transfer, especially during transient operations. This study addresses the effects of thermal inertia on combustion in an HCCI engine. In this study, the control of combustion timing in an HCCI engine is achieved by modulating the residual gas fraction (RGF) while considering the wall temperatures. A multi-cylinder engine simulation with detailed geometry is carried out using a 1-D system model (GT-Power®) that is linked with Simulink®. The model includes a finite element wall temperature solver and is enhanced with original HCCI combustion and heat transfer models. Initially, the required residual gas fraction for optimal BSFC is determined for steady-state operation. The model is then used to derive a map of the sensitivity of optimal residual gas fraction to wall temperature excursions.

This paper investigates series plug-in hybrid electric vehicle (PHEV) behavior during one-day with synthesized representative one-day missions. The amounts of electric energy and fuel consumption are predicted to assess the PHEV impact on the grid with respect to the driving distance and different charging scenarios: (1) charging overnight, (2) charging whenever possible. The representative cycles are synthesized using the extracted information from the real-world driving data in Southeast Michigan gathered through the Field Operational Tests (FOT) conducted by the University of Michigan Transportation Research Institute (UMTRI). The real-world driving data include 4,409 trips covering 830 independent days and temporal distributions of departure and arrival times. The sample size is large enough to represent real-world driving.

Thermal barrier coatings (TBCs) have been of interest since the 1970s for application in internal combustion (IC) engines. Thin TBCs exhibit a temperature swing phenomenon wherein wall temperatures dynamically respond to the transient working-gas temperature throughout the engine cycle, thus reducing the temperature difference driving the heat transfer. Determining these varying wall temperatures is necessary to evaluate and study the effect of coatings on wall heat transfer. This study focuses on developing a 3D computational fluid dynamics (CFD)-finite element analysis (FEA) coupled simulation, or co-simulation, routine to determine the wall temperatures of a piston coated with a thin TBC layer subject to spark ignition combustion heat flux. A CONVERGE 3D-CFD model was used to simulate the combustion process in a single-cylinder, light-duty experimental spark ignition (SI) engine.

Exhaust gas rebreathing is considered to be a practical enabler that could be used in HCCI production engines. Recent experimental work at the University of Michigan demonstrates that the combustion characteristics of an HCCI engine using large amounts of hot residual gas by rebreathing are very sensitive to engine thermal conditions. This computational study addresses HCCI engine operation with rebreathing, with emphasis on the effects of engine thermal conditions during transient periods. A 1-D cycle simulation with thermal networks is carried out under load and speed transitions. A knock integral auto-ignition model, a modified Woschni heat transfer model for HCCI engines and empirical correlations to define burn rate and combustion efficiency are incorporated into the engine cycle simulation model. The simulation results show very different engine behavior during the thermal transient periods compared with steady state.