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The components in a hybrid electric vehicle (HEV) powertrain include the battery pack, an internal combustion engine, and the electric machines such as motors and possibly a generator. These components generate a considerable amount of heat during driving cycles. A robust thermal management system with advanced controller, designed for temperature tracking, is required for vehicle safety and energy efficiency. In this study, a hybridized mid-size truck for military application is investigated. The paper examines the integration of advanced control algorithms to the cooling system featuring an electric-mechanical compressor, coolant pump and radiator fans. Mathematical models are developed to numerically describe the thermal behavior of these powertrain elements. A series of controllers are designed to effectively manage the battery pack, electric motors, and the internal combustion engine temperatures.

Refinements were made to a post-processing technique, termed the Thermal Stratification Analysis (TSA), that couples the mass fraction burned data to ignition timing predictions from the autoignition integral to calculate an apparent temperature distribution from an experimental HCCI data point. Specifically, the analysis is expanded to include all of the mass in the cylinder by fitting the unburned mass with an exponential function, characteristic of the wall-affected region. The analysis-derived temperature distributions are then validated in two ways. First, the output data from CFD simulations are processed with the Thermal Stratification Analysis and the calculated temperature distributions are compared to the known CFD distributions.

The fidelity of the hybrid electric vehicle simulation is increased with the integration of a computationally-efficient finite-element based electric machine model, in order to address optimization of component design for system level goals. In-wheel electric motors are considered because of the off-road military application which differs significantly from commercial HEV applications. Optimization framework is setup by coupling the vehicle simulation to the constrained optimization solver. Utilizing the increased design flexibility afforded by the model, the solver is able to reshape the electric machine's efficiency map to better match the vehicle operation points. As the result, the favorable design of the e-machine is selected to improve vehicle fuel economy and reduce cost, while satisfying performance constraints.

This paper introduces a Hydraulic Linear Engine (HLE) concept and describes a model to simulate instantaneous engine behavior. The United States Environmental Protection Agency has developed an HLE prototype as an evolution of their previous six-cylinder, four-stroke, free-piston engine (FPE) hardware. The HLE design extracts work hydraulically, in a fashion identical to the initial FPE, and is intended for use in a series hydraulic hybrid vehicle. Unlike the FPE, however, the HLE utilizes a crank for improved timing control and increased robustness. Preliminary experimental results show significant speed fluctuations and cylinder imbalance that require careful controls design. This paper also introduces a model of the HLE that exhibits similar behavior, making it an indispensible tool for controls design. Further, the model's behavior is evaluated over a range of operating conditions currently unobtainable by the experimental setup.

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.

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.

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.

This paper proposes a framework to perform design optimization of a series PHEV and investigates the impact of using real-world driving inputs on final design. Real-World driving is characterized from a database of naturalistic driving generated in Field Operational Tests. The procedure utilizes Markov chains to generate synthetic drive cycles representative of real-world driving. Subsequently, PHEV optimization is performed in two steps. First the optimal battery and motor sizes to most efficiently achieve a desired All Electric Range (AER) are determined. A synthetic cycle representative of driving over a given range is used for function evaluations. Then, the optimal engine size is obtained by considering fuel economy in the charge sustaining (CS) mode. The higher power/energy demands of real-world cycles lead to PHEV designs with substantially larger batteries and engines than those developed using repetitions of the federal urban cycle (UDDS).

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.

Stringent fuel economy and emissions regulations have driven development of new mixture preparation technologies and increased spark-ignition engine complexity. Additional degrees of freedom, brought about by devices such as cam phasers and charge motion control valves, enable greater range and flexibility in engine control. This permits significant gains in fuel efficiency and emission control, but creates challenges related to proper engine control and calibration techniques. Accurate experimental characterization of high degree of freedom engines is essential for addressing the controls challenge. In particular, this paper focuses on the evaluation of three experimental residual gas fraction measurement techniques for use in a spark ignition engine equipped with dual-independent variable camshaft phasing (VVT).

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.

The global energy situation, the dependence of the transportation sector on fossil fuels, and a need for rapid response to the global warming challenge, provide a strong impetus for development of fuel efficient vehicle propulsion. The task is particularly challenging in the case of trucks due to severe weight/size constraints. Hybridization is the only approach offering significant breakthroughs in near and mid-term. In particular, the series configuration decouples the engine from the wheels and allows full flexibility in controlling the engine operation, while the hydraulic energy conversion and storage provides exceptional power density and efficiency. The challenge stems from a relatively low energy density of the hydraulic accumulator, and this provides part of the motivation for a simulation-based approach to development of the system power management. The vehicle is based on the HMMWV platform, a 4×4 off-road truck weighing 5112 kg.

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.

Homogenous Charge Compression Ignition (HCCI) engines offer a good potential for achieving high fuel efficiency while virtually eliminating NOx and soot emissions from the exhaust. However, realizing the full fuel economy potential at the vehicle level depends on the size of the HCCI operating range. The usable HCCI range is determined by the knock limit on the upper end and the misfire limit at the lower end. Previously proven high sensitivity of the HCCI process to thermal conditions leads to a hypothesis that combustion chamber deposits (CCD) could directly affect HCCI combustion, and that insight about this effect can be helpful in expanding the low-load limit. A combustion chamber conditioning process was carried out in a single-cylinder gasoline-fueled engine with exhaust re-breathing to study CCD formation rates and their effect on combustion. Burn rates accelerated significantly over the forty hours of running under typical HCCI operating conditions.

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.

One of the major problems limiting the accuracy of piezoelectric transducers for cylinder pressure measurements in an internal-combustion (IC) engine is the thermal shock. Thermal shock is generated from the temperature variation during the cycle. This temperature variation results in contraction and expansion of the diaphragm and consequently changes the force acting on the quartz in the pressure transducer. An empirical equation for compensation of the thermal shock error was derived from consideration of the diaphragm thermal deformation and actual pressure data. The deformation and the resulting pressure difference due to thermal shock are mainly a function of the change in surface temperature and the equation includes two model constants. In order to calibrate these two constants, the pressure inside the cylinder of a diesel engine was measured simultaneously using two types of pressure transducers, in addition to instantaneous wall temperature measurement.

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.

The emerging Variable Valve Timing (VVT) technology complicates the estimation of air flow rate because both intake and exhaust valve timings significantly affect engine's gas exchange and air flow rate. In this paper, we propose to use Artificial Neural Networks (ANN) to model the air flow rate through a 2.4 liter VVT engine with independent intake and exhaust camshaft phasers. The procedure for selecting the network architecture and size is combined with the appropriate training methodology to maximize accuracy and prevent overfitting. After completing the ANN training based on a large set of dynamometer test data, the multi-layer feedforward network demonstrates the ability to represent air flow rate accurately over a wide range of operating conditions. The ANN model is implemented in a vehicle with the same 2.4 L engine using a Rapid Prototype Controller.

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.