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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.

Electrification and hybridization show great potential for improving fuel economy and reducing emission in heavy-duty vehicles. However, high battery cost is unavoidable due to the requirement for large batteries capable of providing high electric power for propulsion. The battery size and cost can be reduced with advanced battery control strategies ensuring safe and robust operation covering infrequent extreme conditions. In this paper, the impact of such a battery control strategy on battery sizing and fuel economy is investigated under various military and heavy-duty driving cycles. The control strategy uses estimated Li-ion concentration information in the electrodes to prevent battery over-charging and over-discharging under aggressive driving conditions. Excessive battery operation is moderated by adjusting allowable battery power limits through the feedback of electrode-averaged Li-ion concentration estimated by an extended Kalman filter (EKF).

This simulation study explores the potential synergy between the HCCI engine system and three hybrid electric vehicle (HEV) configurations, and proposes the supervisory control strategy that maximizes the benefits of combining these two technologies. HCCI operation significantly improves fuel efficiency at part load, while hybridization aims to reduce low load/low speed operation. Therefore, a key question arises: are the effects of these two technologies additive or overlapping? The HEV configurations include two parallel hybrids with varying degrees of electrification, e.g. with a 5kW integrated starter/motor (“Mild”) and with a 10 kW electric machine (“Medium”), and a power-split hybrid. The engine is a dual-mode, SI-HCCI system and the engine map reflects the impact of HCCI on brake specific fuel consumption.

Electrification and hybridization have great potential for improving fuel economy and reducing visual signature or soot emissions in military vehicles. Specific challenges related to military applications include severe duty cycles, large and uncertain energy flows through the system and high thermal loads. A novel supervisory control strategy is proposed to simultaneously mitigate severe engine transients and to reduce high electric current in the battery without oversizing the battery. The described objectives are accomplished by splitting the propulsion power demand through filtering in the frequency domain. The engine covers only low frequency power demand profile while the battery covers high frequency components. In the proposed strategy, the separation filter is systematically designed to identify different frequency components with the consideration of fuel consumption, aggressive engine transients, and battery electric loads.

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.

The attractiveness of the hydraulic hybrid concept stems from the high power density and efficiency of the pump/motors and the accumulator. This is particularly advantageous in applications to heavy vehicles, as high mass translates into high rates of energy flows through the system. Using dry case hydraulic pumps further improves the energy conversion in the system, as they have 1-4% better efficiency than traditional wet-case pumps. However, evacuation of fluid from the case introduces air bubbles and it becomes imperative to address the deaeration problems. This research develops a bubble elimination efficiency testing apparatus (BEETA) to establish quantitative results characterizing bubble removal from hydraulic fluid in a cyclone deaeration device. The BEETA system mixes the oil and air according to predetermined ratio, passes the mixture through a cyclone deaeration device, and then measures the concentration of air in the exiting fluid.

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.

This paper proposes a simulation based methodology to assess plug-in hybrid vehicle (PHEV) behavior over 24-hour periods. Several representative 24-hour missions comprise naturalistic cycle data and information about vehicle resting time. The data were acquired during Filed Operational Tests (FOT) of a fleet of passenger vehicles carried out by the University of Michigan Transportation Research Institute (UMTRI) for safety research. Then, PHEV behavior is investigated using a simulation with two different charging scenarios: (1) Charging overnight; (2) Charging whenever possible. Charging/discharging patterns of the battery as well as trends of charge depleting (CD) and charge sustaining (CS) modes at each scenario were assessed. Series PHEV simulation is generated using Powertrain System Analysis Toolkit (PSAT) developed by Argonne National Laboratory (ANL) and in-house Matlab codes.

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.

This paper presents the development of an electrochemical aging model of LiFePO4-Graphite battery based on single particle (SP) model. Solid electrolyte interphase (SEI) growth is considered as the aging mechanism. It is intended to provide both sufficient fidelity and computational efficiency required for integration within the HEV power management optimization framework. The model enables assessment of the battery aging rate by considering instantaneous lithium ion surface concentration rather than average concentration, thus enhancing the fidelity of predictions. In addition, an approximate analytical method is applied to speed up the calculation while preserving required accuracy. Next, this aging model are illustrated two applications. First is hybrid electric powertrain system model integration and simulation.

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.

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.

This study investigates the impact of transient engine operation on the emissions formed during a tip-in procedure. A medium-duty production V-8 diesel engine is used to conduct experiments in which the rate of pedal position change is varied. Highly-dynamic emissions instrumentation is implemented to provide real-time measurement of NOx and particulate. Engine subsystems are analyzed to understand their role in emissions formation. As the rate of pedal position change increases, the emissions of NOx and particulates are affected dramatically. An instantaneous load increase was found to produce peak NOx values 1.8 times higher and peak particulate concentrations an order of magnitude above levels corresponding to a five-second ramp-up. The results provide insight into relationship between driver aggressiveness and diesel emissions applicable to development of drive-by-wire systems. In addition, they provide direct guidance for devising low-emission strategies for hybrid vehicles.