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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.

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.

In military applications, diesel engines are required to achieve high power outputs and therefore must operate at high loads. This high load operation leads to high piston component temperatures and heat rejection rates limiting the packaged power density of the powertrain. To help predict and understand these constraints, as well as their effects on performance, a thermodynamic engine model coupled to a finite element heat conduction solver is proposed and validated in this work. The finite element solver is used to calculate crank angle resolved, spatially averaged piston temperatures from in-cylinder heat transfer calculations. The calculated piston temperatures refine the heat transfer predictions as well requiring iteration between the thermodynamic model and finite element solver.

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.

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.

Electrification of off-road vehicle powertrains can increase mobility, improve energy efficiency, and enable new utility by providing high amounts of electrical power for auxiliary devices. These vehicles often operate in extreme temperature conditions at low ground speeds and high power levels while also having significant cooling airpath restrictions. The restrictions are a consequence of having grilles and/or louvers in the airpath to prevent damage from the operating environment. Moreover, the maximum operating temperatures for high voltage electrical components, like batteries, motors, and power-electronics, can be significantly lower than those of the internal combustion engine. Rejecting heat at a lower temperature gradient requires higher flow rates of air for effective heat exchange to the operating environment at extreme temperature conditions.

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.

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.

This paper presents an Organic Rankine Cycle (ORC) system model for heavy-duty diesel (HDD) applications. The dynamic, physics-based model includes: heat exchangers for parallel exhaust and EGR circuits, compressible vapor working fluid, distribution and flow control valves, a high pressure pump, and a reservoir. A finite volume method is used to model the evaporator, and a pressure drop model is included to improve the accuracy of predictions. Experimental results obtained on a prototype ORC system are used for model calibration and validation. Comparison of predicted and measured values under steady-state conditions is pursued first, followed by the analysis of selected transient events. Validation reveals the model’s ability to track real-world temperature and pressure dynamics of the ORC system. Therefore, this modeling framework is suitable for future system design studies, optimization of ORC power generation, and as a basis for development of control-oriented ORC models.

Low pressure (LP) and cooled EGR systems are capable of increasing fuel efficiency of turbocharged gasoline engines, however they introduce control challenges. Accurate exhaust pressure modeling is of particular importance for real-time feedforward control of these EGR systems since they operate under low pressure differentials. To provide a solution that does not depend on physical sensors in the exhaust and also does not require extensive calibration, a coupled temperature and pressure physics-based model is proposed. The exhaust pipe is split into two different lumped sections based on flow conditions in order to calculate turbine-outlet pressure, which is the driving force for LP-EGR. The temperature model uses the turbine-outlet temperature as an input, which is known through existing engine control models, to determine heat transfer losses through the exhaust.

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%.

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.

An experimental study has been carried out to provide qualitative and quantitative insight into gas to wall heat transfer in a gasoline fueled Homogeneous Charge Compression Ignition (HCCI) engine. Fast response thermocouples are embedded in the piston top and cylinder head surface to measure instantaneous wall temperature and heat flux. Heat flux measurements obtained at multiple locations show small spatial variations, thus confirming relative uniformity of in-cylinder conditions in a HCCI engine operating with premixed charge. Consequently, the spatially-averaged heat flux represents well the global heat transfer from the gas to the combustion chamber walls in the premixed HCCI engine, as confirmed through the gross heat release analysis. Heat flux measurements were used for assessing several existing heat transfer correlations. One of the most popular models, the Woschni expression, was shown to be inadequate for the HCCI engine.

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.

Commercial vehicles transport the majority of the inland freight in US and a significant number of passengers. They are large fuel consumers as they operate a large number of hours per day, pulling heavy loads. The increasing fuel price and the Green House Gas emission regulation have provided a strong impetus for new technologies capable of improving the commercial vehicle fuel economy. Among others, optimized powertrain control can improve the vehicle fuel economy, particularly if it is based on accurate information about the instantaneous load demand. Furthermore, model-based online vehicle parameter estimator is critical for implementation of an adaptive vehicle controller. While vehicle mass estimation has been successfully demonstrated, rolling resistance and aerodynamic drag estimation has not been fully explored yet. This paper examines this problem using model-based approach with a supervisory data extraction scheme.

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.

Spark ignition knock is highly sensitive to changes in intake air temperature. Hot surface temperatures due to ceramic thermal barrier coatings increase knock propensity by elevating the incoming air temperature, thus mitigating the positive impacts of low heat transfer losses by requiring spark retard to avoid knock. Low thermal inertia coatings (i.e. Temperature swing coatings) have been proposed as a means of reducing or eliminating the open cycle charge heating penalty of traditional TBCs through a combination of low thermal conductivity and low volumetric heat capacity materials. However, in order to achieve a meaningful gain in efficiency, a significant fraction of the combustion chamber must be coated. In this study, a coated piston and intake and exhaust valves with coated combustion faces, backsides, and stems are installed in a single-cylinder research engine to evaluate the effect of high coated fractions of the combustion chamber in a knock-sensitive architecture.

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.

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.