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Electric transportation has the potential of mitigating CO2 emissions and reduce fuel needs. One of the challenges for the growth of this industry is limited range and efficiency of the vehicles associated with battery storage systems and electric drive technology. High voltage systems are expected to increase efficiency and then vehicle mileage, however this increases the severity of the fault conditions, especially in case of short circuit. Melting fuse is commonly used for the purpose of protection in electrified vehicles, while it is effective and reliable, there are several shortcomings such as lack of precision, effect of ambient temperature, bulky, interruption time depending on the fault condition etc. Additionally, the on-board DC power distribution system (PDS) is characterized by low impedance, in this environment fuses are not able to limit the fault current leading to damage of electronics and hazard for the battery pack.

The automotive industry is striving to adopt model-based engine design and optimization procedures to reduce development time and costs. In this scenario, first-principles gas dynamic models predicting the mass, energy and momentum transport in the engine air path system with high accuracy and low computation effort are extremely important today for performance prediction, optimization and cylinder charge estimation and control. This paper presents a comparative study of two different modeling approaches to predict the one-dimensional unsteady compressible flow in the engine air path system. The first approach is based on a quasi-3D finite volume method, which relies on a geometrical reconstruction of the calculation domain using networks of zero-dimensional elements. The second approach is based on a model-order reduction procedure that projects the nonlinear hyperbolic partial differential equations describing the 1D unsteady flow in engine manifolds onto a predefined basis.

Model-based design is a collection of practices in which a system model is at the center of the development process, from requirements definition and system design to implementation and testing. This approach provides a number of benefits such as reducing development time and cost, improving product quality, and generating a more reliable final product through the use of computer models for system verification and testing. Model-based design is particularly useful in automotive control applications where ease of calibration and reliability are critical parameters. A novel application of the model-based design approach is demonstrated by The Ohio State University (OSU) student team as part of the Challenge X advanced vehicle development competition. In 2008, the team participated in the final year of the competition with a highly refined hybrid-electric vehicle (HEV) that uses a through-the-road parallel architecture.

Traditionally in the United States, Diesel engines have negative connotations, primarily due to their association with heavy duty trucks, which are wrongly characterized as “dirty.” Diesel engines are more energy efficient and produce less carbon dioxide than gasoline engines, but their particulate and NOx emissions are more difficult to reduce than spark ignition engines. To tackle this problem, a number of after-treatment technologies are available, such as Diesel Lean NOx Traps (LNTs)), which reduces oxides of nitrogen, and the Diesel particulate filter (DPF), which reduces particulate matter. Sophisticated control techniques are at the heart of these technologies, thus making Diesel engines run cleaner. Another potentially unattractive aspect of Diesel engines is noise.

Strong dependency on crude oil in most areas of modern transportation needs lead into a significant consumption of petroleum resources over many decades. In order to maximize the effective use of remaining resources, various types of powertrain topologies, such as hybrid configurations among fuel cell, electric battery as well as conventional IC engine, have been proposed and tested out for number of vehicle classes including a personal commuting vehicle. In this paper the vehicle parameters are based on a typical commercial sub-compact vehicle (FIAT Panda) and energy needs are estimated on the sized powertrain. The main control approach is divided in two categories: off-line global optimization with dynamic programming (DP, not implementable in real time), and on-line Proportional and Feed-Forward with PI controllers. The proposed control approaches are developed both for charge-sustaining and charge-depleting mode and sample results are shown and compared.

Experimental results are presented for a technique of converting Diesel fuel to a gas stream rich in carbon monoxide and hydrogen suitable for Lean NOx Trap (LNT) regeneration. The device is relatively simple and relies upon a premixed, rich flame to generate gas with 4.5% H2 and 10% CO. The device, referred to as a flame reformer, offers a number of advantages over other methods of reductant generation for bypass regeneration LNT systems. Specifically, the device offers rapid dynamic response, potential lower cost, with a similar level of performance to other proposed methods of reductant generation.

In this paper, the detection and isolation of actuator faults (both measured and commanded) occurring in the engine breathing and the fueling systems of a spark-ignition direct-injection (SIDI) engine are described. The breathing system in an SIDI engine usually consists of a fresh air induction path via an electronically controlled throttle (ECT) and an exhaust gas recirculation (EGR) path via an EGR valve. They are dynamically coupled through the intake manifold to form a gas mixture, which eventually enters the engine cylinders for a subsequent combustion process. Meanwhile, the fueling system is equipped with a high-pressure common-rail injection for a precise control of the fuel quantity directly injected into the engine cylinders. Since the coupled system is highly nonlinear in nature, the fault diagnosis will be performed by generating residuals based on multiple nonlinear observers.

With the introduction of common rail fuel injection system enabling multiple injections per stroke and stringent pollutant emission standards, the optimization and calibration of modern compression ignition direct injection (CIDI) engines become more complex. Thus, a simple and efficient tool for CIDI combustion simulation with arbitrary fuel injection profile is required today. A crank-angle resolved combustion model was developed and validated by using a fuel injection rig and an engine dynamometer for the parameterization. With the calibrated models, accurate prediction of the in-cylinder pressure and NOx and also a virtual dynamometer mapping are possible. The results from these virtual mappings can be used to calibrate the black-box combustion models in control-oriented, dynamic Mean Value Models (MVM).

This year, in the third year of FutureTruck competition, the Ohio State University team has taken the challenge to convert a 2002 Ford Explorer into a more fuel efficient and environmentally friendly SUV. This goal was achieved by use of a post-transmission, charge sustaining, parallel hybrid diesel-electric drivetrain. The main power source is a 2.5-liter, 103 kW advanced CIDI engine manufactured by VM Motori. A 55 kW Ecostar AC induction electric motor provides the supplemental power. The powertrain is managed by a state of the art supervisory control system which optimizes powertrain characteristics using advanced energy management and emission control algorithms. A unique driver interface implementing advanced telematics, and an interior designed specifically to reduce weight and be more environmentally friendly add to the utility of the vehicle as well as the consumer appeal.

The simulation and evaluation of land vehicle performance requires accurate representations of driving conditions. Currently, many driving cycles have been developed and used in the determination of vehicle fuel economy and emission performance. These driving cycles are typically defined as vehicle speed and power trajectories over time. However, most of the standard driving cycles are short in duration and distance and inadequate in representing a wide range of actual driving conditions. There are also many specialized driving cycles designed for specific types of vehicles, but these are often not applicable to more than a specific class of vehicles. Moreover, more detailed driving schedules are often kept as proprietary information within the vehicle manufacturers.

This paper presents a general formulation of the instantaneous power split between a fuel cell and an electrical accumulator in a charge-sustaining fuel cell hybrid vehicle. The approach proposed in this paper is based on the ECMS (Equivalent Consumption Minimization Strategy) control strategy previously developed for parallel hybrid vehicle applications suitable for real time application and allowing the overall minimization of hydrogen consumption while meeting the driver demand. This control strategy has been applied to a representative hybrid PEM (Proton Exchange Membrane) fuel cell mid-size vehicle. Using a Hybrid Fuel Cell vehicle simulator, the vehicle performance and energy requirements are estimated. The results provided by the ECMS control strategy approach are also compared to a more basic approach.

In recent years, the increasing interest and requirements for improved engine diagnostics and control has led to the implementation of several different sensing and signal processing technologies. In order to optimize the performance and emission of an engine, detailed and specified knowledge of the combustion process inside the engine cylinder is required. In that sense, the torque generated by each combustion event in an IC engine is one of the most important variables related to the combustion process and engine performance. This paper introduces torque estimation techniques in the real-time basis for engine control applications using the measurement of crankshaft speed variation. The torque estimation scheme presented in this paper consists of two entirely different approaches, “Stochastic Analysis” and “Frequency Analysis”.

The aim of this paper is to describe a unified approach to modeling the energy efficiency and power flow characteristics of energy storage and energy conversion elements used in hybrid vehicles. Hybrid vehicle analysis and design is concerned with the storage of energy in three domains - chemical, mechanical, and electrical - and on energy conversions between these domains. The paper presents the physical and mathematical basis of this modeling approach, as well as a modular simulator that embodies the same basic principles. The use of the simulator as an analysis tool is demonstrated through the conceptual design of a sport-utility hybrid drivetrain.

Actual stringent regulations on emission level imply highly efficient control strategies, which can be based on the instantaneous engine torque or the in-cylinder pressure. To reach this objective, while avoiding costly direct measurements, the estimation of one of these variables is required. In this paper, two methods are presented based on the correlation between the crankshaft velocity and the indicated torque or pressure. In the “mechanistic method”, the model based on the dynamics of the reciprocating engine and on a correlation with the combustion process provides a relationship between the fluctuating component of the instantaneous crankshaft acceleration and the average indicated torque of the firing cylinders. Thus, an indicated torque signature of each cylinder can be estimated from the observation of the crankshaft acceleration.

The evolution of the flow field inside an IC engine during the intake stroke was studied using 2 different experimental techniques, namely the 2–D Particle Image Velocimetry (2–D PIV) and 3–D Particle Tracking Velocimetry (3–D PTV) techniques. Both studies were conducted using a water analog engine simulation rig. The head tested was a typical pent–roof head geometry with two intake valves and one exhaust valve, and the simulated engine operating point corresponded to an idle condition. For both the 2–D PIV and 3–D PTV experiments, high–speed CCD cameras were used to record the motion of the flow tracer particles. The camera frame rate was adjusted to correspond to 1/4° of crank angle (CA), hence ensuring excellent temporal resolution for velocity calculations. For the 2–D PIV experiment, the flow field was illuminated by an Argon–ion laser with laser–sheet forming optics and this laser sheet was introduced through a transparent piston crown to illuminate the center tumble plane.

Over the last decade, many methods have been proposed for estimating the in-cylinder combustion pressure or the torque from instantaneous crankshaft speed measurements. However, such approaches are typically computationally expensive. In this paper, an entirely different approach is presented to allow the real-time estimation of the in-cylinder pressures based on crankshaft speed measurements. The technical implementation of the method will be presented, as well as extensive results obtained for a V-6 S.I. engine while varying spark timing, engine speed, engine load and EGR. The method allows to estimate the in-cylinder pressure with an average estimation error of the order of 1 to 2% of the peak pressure. It is very general in its formulation, is statistically robust in the presence of noise, and computationally inexpensive.

Typically, the combustion analysis for S.I. engines is limited to the determination of the apparent heat release from in-cylinder pressure measurements, effectively using a single zone approach with constant properties determined at some average temperature. In this paper, we follow an approach consistent with the engine modeling approach (i.e., reverse modeling) to extract heat release rate from combustion pressure data. The experimental data used here solely consists of quantities measured in a typical engine dynamometer tests, namely the crank-angle resolved cylinder pressure, as well as global measurements of the A/F ratio, engine speed, load, EGR, air mass flow rate and temperature and exhaust emissions. We then perform a two-zone, crank-angle resolved analysis of the pressure data using variable composition and properties.