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Boosted Homogeneous Charge Compression Ignition (HCCI) has been modeled and has demonstrated the potential to extend the engine's upper load limit. A commercially available engine simulation software (GT-PowerÖ) coupled to the University of Michigan HCCI combustion and heat transfer correlations was used to model a 4-cylinder boosted HCCI engine with three different boosting configurations: turbocharging, supercharging and series turbocharging. The scope of this study is to identify the best boosting approach in order to extend the HCCI engine's operating range. The results of this study are consistent with the literature: Boosting helps increase the HCCI upper load limit, but matching of turbochargers is a problem. In addition, the low exhaust gas enthalpy resulting from HCCI combustion leads to high pressures in the exhaust manifold increasing pumping work. The series turbocharging strategy appears to provide the largest load range extension.

This paper investigates the impact of battery cooling ancillary losses on fuel economy, and optimal control strategy for a series hybrid electric truck with consideration of cooling losses. Battery thermal model and its refrigeration-based cooling system are integrated into vehicle model, and the parasitic power consumption from cooling auxiliaries is considered in power management problem. Two supervisory control strategies are compared. First, a rule-based control strategy is coupled with a thermal management strategy; it controls power system and cooling system separately. The second is optimal control strategy developed using Dynamic Programming; it optimizes power flow with consideration of both propulsion and cooling requirement. The result shows that battery cooling consumption could cause fuel economy loss as high as 5%.

Abundant supply of Natural Gas (NG) is U.S. and cost-advantage compared to diesel provides impetus for engineers to use alternative gaseous fuels in existing engines. Dual-fuel natural gas engines preserve diesel thermal efficiencies and reduce fuel cost without imposing consumer range anxiety. Increased complexity poses several challenges, including the transient response of an engine with direct injection of diesel fuel and injection of Compressed Natural Gas (CNG) upstream of the intake manifold. A 1-D simulation of a Cummins ISX heavy duty, dual-fuel, natural gas-diesel engine is developed in the GT-Power environment to study and improve transient response. The simulated Variable Geometry Turbine (VGT)behavior, intake and exhaust geometry, valve timings and injector models are validated through experimental results. A triple Wiebe combustion model is applied to characterize experimental combustion results for both diesel and dual-fuel operation.

There are many methods developed over the past decade to solve the problem of energy management control for hybrid electric vehicles. A novel method is introduced in this paper to address the same problem which reduces the problem to a set of physical equations and maps. In simple terms, this method directly calculates the actual cost or savings in fuel energy from the generation or usage of electric energy. It also calculates the local optimum electric power that yields higher electric fuel savings (EFS) or lower electric fuel cost (EFC) in the fuel energy that is spent for driving the vehicle (which in general does not take the system to the lowest engine Brake Specific Fuel Consumption (BSFC)). Based on this approach, a control algorithm is developed which attempts to approach the global optimum over a drive cycle.

The pursuit of greater fuel economy in internal combustion engines requires the optimization of all subsystems including thermal management. The reduction of cooling power required by the electromechanical coolant pump, radiator fan(s), and thermal valve demands real time control strategies. To maintain the engine temperature within prescribed limits for different operating conditions, the continual estimation of the heat removal needs and the synergistic operation of the cooling system components must be accomplished. The reductions in thermal management power consumption can be achieved by avoiding unnecessary overcooling efforts which are often accommodated by extreme thermostat valve positions. In this paper, an optimal nonlinear controller for a military M-ATV engine cooling system will be presented. The prescribed engine coolant temperature will be tracked while minimizing the pump, fan(s), and valve power usage.

Homogenous Charge Compression Ignition (HCCI) combustion offers significant efficiency improvements compared to conventional spark ignition engines. However, due to the nature of HCCI combustion, traditional HCCI combustion can be realized only in a limited operating range. In order to maximize fuel economy benefits the HCCI operating range needs to be extended to higher loads. One immediate benefit is to maximize the portion of the standard driving cycles (NEDC, FTP, etc.) that can be run with HCCI combustion, so that transitions between SI operation and HCCI operation can be avoided. The HCCI operation at high load range is typically limited by a trade-off between combustion noise and combustion stability. In a previous research, we showed how to improve this trade-off using spark-assisted HCCI combustion strategy, and concluded that the HCCI high load operation is limited by the air availability due to a low lift cam when spark-assisted HCCI combustion was applied.

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.

In this work, a novel opposed piston architecture is proposed where one crankshaft rotates at twice the speed of the other. This results in one piston creating a 2-stroke profile and another with a 4-stroke profile. In this configuration, the slower piston operates in the 2-stroke CAD domain, while the faster piston completes 2 reciprocating cycles in the same amount of time (4-stroke). The key benefit of this cycle is that the 4-stroke piston increases the rate of compression and expansion (dV/dθ), which lowers the combustion-induced pressure rise rate after top dead center (crank angle location of minimum volume). Additionally, it lowers in-cylinder temperatures and pressures more rapidly, resulting in a lower residence time at high temperatures, which reduces residence time for thermal NOx formation and reduces the temperature differential between the gas and the wall, thereby reducing heat transfer.

In-cylinder surface temperature is of heightened importance for Homogeneous Charge Compression Ignition (HCCI) combustion since the combustion mechanism is thermo-kinetically driven. Thermal Barrier Coatings (TBCs) selectively manipulate the in-cylinder surface temperature, providing an avenue for improving thermal and combustion efficiency. A surface temperature swing during combustion/expansion reduces heat transfer losses, leading to more complete combustion and reduced emissions. At the same time, achieving a highly dynamic response sidesteps preheating of charge during intake and eliminates the volumetric efficiency penalty. The magnitude and temporal profile of the dynamic surface temperature swing is affected by the TBC material properties, thickness, morphology, engine speed, and heat flux from the combustion process. This study follows prior work of authors with Yttria Stabilized Zirconia, which systematically engineered coatings for HCCI combustion.

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.

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.

Extending the operating range of the gasoline HCCI engine is essential for achieving desired fuel economy improvements at the vehicle level, and it requires deep understanding of the thermal conditions in the cylinder. Combustion chamber deposits (CCD) have been previously shown to have direct impact on near-wall phenomena and burn rates in the HCCI engine. Hence, the objectives of this work are to characterize thermal properties of deposits in a gasoline HCCI engine and provide foundation for understanding the nature of their impact on autoignition and combustion. The investigation was performed using a single-cylinder engine with re-induction of exhaust instrumented with fast-response thermocouples on the piston top and the cylinder head surface. The measured instantaneous temperature profiles changed as the deposits grew on top of the hot-junctions.

Homogenous Charge Compression Ignition (HCCI) combustion offers significant efficiency improvements compared to conventional gasoline engines. However, due to the nature of HCCI combustion, traditional HCCI engines show some degree of sensitivity to in-cylinder thermal conditions; thus higher cylinder-to-cylinder variation was observed especially at low load and high load operating conditions due to different injector characteristics, different amount of reforming as well as non-uniform EGR distribution. To address these issues, a cylinder balancing control strategy was developed for a multi-cylinder engine. In particular, the cylinder balancing control strategy balances CA50 and AF ratio at high load and low load conditions, respectively. Combustion noise was significantly reduced at high load while combustion stability was improved at low load with the cylinder balancing control.

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 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.

Heat rejection in ground vehicle propulsion systems remains a challenge given variations in powertrain configurations, driving cycles, and ambient conditions as well as space constraints and available power budgets. An optimization strategy is proposed for engine radiator geometry size scaling to minimize the cooling system power consumption while satisfying both the heat removal rate requirement and the radiator dimension size limitation. A finite difference method (FDM) based on a heat exchanger model is introduced and utilized in the optimization design. The optimization technique searches for the best radiator core dimension solution over the design space, subject to different constraints. To validate the proposed heat exchanger model and optimization algorithm, a heavy duty military truck engine cooling system is investigated.

This study investigates a novel approach towards boosted HCCI operation, which makes use of all engine system components in order to maximize overall efficiency. Four-cylinder boosted HCCI engines have been modeled employing valve strategies and turbomachines that enable high load operation with significant efficiency benefits. A commercially available engine simulation software, coupled to the University of Michigan HCCI combustion and heat transfer correlations, was used to model the HCCI engines with three different boosting configurations: turbocharging, variable geometry turbocharging and combined supercharging with turbocharging. The valve strategy features switching from low-lift Negative Valve Overlap (NVO) to high-lift Positive Valve Overlap (PVO) at medium loads. The new operating approach indicates that heating of the charge from external compression is more efficient than heating by residual gas retention strategies.

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.

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.