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High hydrocarbon (HC) emission during a cold start still remains one of the major emission control challenges for spark ignition (SI) engines in spite of about three decades of research in this area. This paper proposes a cold start HC emission control strategy based on a reduced order modeling technique. A novel singular perturbation approximation (SPA) technique, based on the balanced realization principle, is developed for a nonlinear experimentally validated cold start emission model. The SPA reduced model is then utilized in the design of a model-based sliding mode controller (SMC). The controller targets to reduce cumulative tailpipe HC emission using a combination of fuel injection, spark timing, and air throttle / idle speed controls. The results from the designed multi-input multi-output (MIMO) reduced order SMC are compared with those from a full order SMC. The results show the reduced SMC outperforms the full order SMC by reducing both engine-out and tailpipe HC emission.

Electronic throttle control is an integral part of an engine electronic control unit (ECU) that directly affects vehicle fuel economy, drivability, and engine-out emissions by managing engine torque and air-fuel ratio through adjusting intake charge flow to the engine. The highly nonlinear dynamics of the throttle body call for nonlinear control techniques that can be implemented in real-time and are also robust to controller implementation imprecision. Discrete sliding mode control (DSMC) is a computationally efficient controller design technique which can handle systems with high degree of nonlinearity. In this paper, a generic robust discrete sliding mode controller design is proposed and experimentally verified for the throttle position tracking problem. In addition, a novel method is used to predict and incorporate the sampling and quantization imprecisions into the DSMC structure. First, a nonlinear physical model for an electromechanical throttle body is derived.

The influence of spark plug orientation on early flame kernel development is investigated in an optically accessible gasoline direct injection homogeneous charged spark ignition engine. This investigation provides visual understanding and statistical characterization of how spark plug orientation impacts the early flame kernel and thus combustion phasing and engine performance. The projected images of flame kernel were captured through natural flame chemiluminescence with a high-speed camera at 10,000 frames per second, and the ignition secondary discharge voltage and current were measured with a 10 MHz DAQ system. The combustion metrics were determined using measurement from a piezo-electric in-cylinder pressure transducer and real-time engine combustion analyzer. Three spark plug orientations with two different electrode designs were studied. The captured images of the flame were processed to yield 2D and 1D probability distributions.

Low Temperature Combustion (LTC) engines are promising to improve powertrain fuel economy and reduce NOx and soot emissions by improving the in-cylinder combustion process. However, the narrow operating range of LTC engines limits the use of these engines in conventional powertrains. The engine’s limited operating range can be improved by taking advantage of electrification in the powertrain. In this study, a multi-mode LTC-SI engine is integrated with a parallel hybrid electric configuration, where the engine operation modes include Homogeneous Charge Compression Ignition (HCCI), Reactivity Controlled Compression Ignition (RCCI), and conventional Spark Ignition (SI). The powertrain controller is designed to enable switching among different modes, with minimum fuel penalty for transient engine operations.

This paper investigates an optimal design of a diesel engine and after-treatment systems for a series hybrid electric forklift application. A holistic modeling approach is developed in GT-Suite® to establish a model-based hardware definition for a diesel engine and an after-treatment system to accurately predict engine performance and emissions. The used engine model is validated with the experimental data. The engine design parameters including compression ratio, boost level, air-fuel ratio (AFR), injection timing, and injection pressure are optimized at a single operating point for the series hybrid electric vehicle, together with the performance of the after-treatment components. The engine and after-treatment models are then coupled with a series hybrid electric powertrain to evaluate the performance of the forklift in the standard VDI 2198 drive cycle.

Robust control of combustion phasing in Homogenous Charge Compression Ignition (HCCI) engines is a well-recognized challenge limiting the automotive industry for exploiting HCCI benefits in mass production vehicles. Real-time model-based control of combustion phasing is the key to tackle this daunting challenge. In this paper, a new control oriented model is developed for predicting HCCI combustion phasing over a range of engine operation. The model is validated against the experimental data from a single cylinder Ricardo engine. A model-based integral state feedback controller is designed to control HCCI combustion phasing by modulating the ratio of two Primary Reference Fuels (PRFs). The controller's performance is compared with a manually tuned proportional integral controller.

One major challenge in Homogeneous Charge Compression Ignition (HCCI) combustion is the difficulty in controlling the timing of auto-ignition which is dependant on mixture conditions. Understanding the effect of modifying the properties of the engine charge on the start of combustion is essential to be able to predict and control the auto-ignition timing. The purpose of this work is to develop a realtime model for predicting HCCI auto-ignition timing. The standard Livengood and Wu Knock-Integral Method (KIM) is modified to work with values that are easier to measure compared with the instantaneous in-cylinder parameters required in the original KIM. This modified Knock-Integral Method (MKIM) is developed and is then parameterized using HCCI Thermokinetic Kinetic Model (TKM) simulations for a single cylinder engine. Estimating the MKIM parameters is done using an off-line optimization technique.

Today, an increasing emphasis is being placed on vehicle transient operation improvement to accomplish better drivability and lower emission and fuel consumption. In this regard, dynamic simulatory model of powertrain-vehicle is a stepping-stone on the path to achieve this goal. In this study, a complete powertrain-vehicle model has been developed to predict vehicle performance and fuel consumption, with careful attention given to the engine dynamics (dynamic of air and fuel flows into the intake manifold, and crankshaft transient response). The model has been experimentally identified and validated for “Paykan 1600i”. Since there is a good agreement between vehicle test and simulation results, the model proposed in this study can be used in design and performance evaluation of vehicle powertrain system.

In the last three decades, the dynamic modeling of internal combustion engines has played critical roles in engine management systems design. This paper outlines a nonlinear dynamic engine model of a port-fuel injected engine, which can be used for control algorithm development. This engine model predicts the mean engine brake torque as a function of engine controls (i.e. throttle angle, spark advance, fuel flow rate).The model has been experimentally identified and validated for a 1.6 liter engine called “Paykan”. In addition, the sensitivity analysis of the model with respect to its parameters perturbation has been accomplished.

An accurate estimation of cycle-by-cycle in-cylinder mass and the composition of the cylinder charge is required for spark-ignition engine transient control strategies to obtain required torque, Air-Fuel-Ratio (AFR) and meet engine pollution regulations. Mass Air Flow (MAF) and Manifold Absolute Pressure (MAP) sensors have been utilized in different control strategies to achieve these targets; however, these sensors have response delay in transients. As an alternative to air flow metering, in-cylinder pressure sensors can be utilized to directly measure cylinder pressure, based on which, the amount of air charge can be estimated without the requirement to model the dynamics of the manifold.

Reactivity Controlled Compression Ignition (RCCI) is a promising dual-fuel Low Temperature Combustion (LTC) mode with significant potential for reducing NOx and particulate emissions while improving or maintaining thermal efficiency compared to Conventional Diesel Combustion (CDC) engines. The large reactivity difference between diesel and Natural Gas (NG) fuels provides a strong control variable for phasing and shaping combustion heat release. In this work, the Brake Thermal Efficiencies (BTE), emissions and combustion characteristics of a light duty 1.9L, four-cylinder diesel engine operating in single fuel diesel mode and in Diesel-NG RCCI mode are investigated and compared. The engine was operated at speeds of 1300 to 2500 RPM and loads of 1 to 7 bar BMEP. Operation was limited to 10 bar/deg Maximum Pressure Rise Rate (MPRR) and 6% Coefficient of Variation (COV) of IMEP.

Low Temperature Combustion (LTC) engines are promising to improve powertrain fuel economy and reduce NOx and soot emissions by improving the in-cylinder combustion process. However, the narrow operating range of LTC engines limits the use of these engines in conventional powertrains. Extended range electric vehicles (EREVs), by decoupling the engine from the drivetrain, allows the engine to operate in a limited operating range; thus, EREVs offer an ideal platform for realizing the advantages of LTC engines. In this study, the global optimum fuel economy improvement of an experimentally developed 2-liter multi-mode LTC engine in a series EREV is investigated. The engine operation modes include Homogeneous-Charge Compression Ignition (HCCI), Reactivity Controlled Compression Ignition (RCCI), and conventional Spark Ignition (SI).

The effect of flow direction towards the spark plug electrodes on ignition parameters is analyzed using an innovative spark aerodynamics fixture that enables adjustment of the spark plug gap orientation and plug axis tilt angle with respect to the incoming flow. The ignition was supplied by a long discharge high energy 110 mJ coil. The flow was supplied by compressed air and the spark was discharged into the flow at varying positions relative to the flow. The secondary ignition voltage and current were measured using a high speed (10MHz) data acquisition system, and the ignition-related metrics were calculated accordingly. Six different electrode designs were tested. These designs feature different positions of the electrode gap with respect to the flow and different shapes of the ground electrodes. The resulting ignition metrics were compared with respect to the spark plug ground strap orientation and plug axis tilt angle about the flow direction.

Verification and validation (V&V) are essential stages in the design cycle of industrial controllers to remove the gap between the designed and implemented controller. In this study, a model-based adaptive methodology is proposed to enable easily verifiable controller design based on the formulation of a sliding mode controller (SMC). The proposed adaptive SMC improves the controller robustness against major implementation imprecisions including sampling and quantization. The application of the proposed technique is demonstrated on the engine cold start emission control problem in a mid-size passenger car. The cold start controller is first designed in a single-input single-output (SISO) structure with three separate sliding surfaces, and then is redesigned based on a multiinput multi-output (MIMO) SMC design technique using nonlinear balanced realization.

Exergy or availability is the potential of a system to do work. In this paper, an innovative exergy-based control approach is presented for Internal Combustion Engines (ICEs). An exergy model is developed for a Homogeneous Charge Compression Ignition (HCCI) engine. The exergy model is based on quantification of the Second Law of Thermodynamic (SLT) and irreversibilities which are not identified in commonly used First Law of Thermodynamics (FLT) analysis. An experimental data set for 175 different ICE operating conditions is used to construct the SLT efficiency maps. Depending on the application, two different SLT efficiency maps are generated including the applications in which work is the desired output, and the applications where Combined Power and Exhaust Exergy (CPEX) is the desired output. The sources of irreversibility and exergy loss are identified for a single cylinder Ricardo HCCI engine.

Real-time control of Reactivity Controlled Compression Ignition (RCCI) during engine load and speed transient operation is challenging, since RCCI combustion phasing depends on nonlinear thermo-kinetic reactions that are controlled by dual-fuel reactivity gradients. This paper discusses the design and implementation of a real-time closed-loop combustion controller to maintain optimum combustion phasing during RCCI transient operations. New algorithms for real-time in-cylinder pressure analysis and combustion phasing calculations are developed and embedded on a Field Programmable Gate Array (FPGA) to compute RCCI combustion and performance metrics on cycle-by-cycle basis. This cycle-by-cycle data is then used as a feedback to the combustion controller, which is implemented on a real-time processor. A computationally efficient algorithm is introduced for detecting Start of Combustion (SOC) for the High Temperature Heat Release (HTHR) or main-stage heat release.

Precise cycle-to-cycle control of combustion is the major challenge to reduce fuel consumption in Homogenous Charge Compression Ignition (HCCI) engines, while maintaining low emission levels. This paper outlines a framework for simultaneous control of HCCI combustion phasing and Indicated Mean Effective Pressure (IMEP) on a cycle-to-cycle basis. A dynamic control model is extended to predict behavior of HCCI engine by capturing main physical processes through an HCCI engine cycle. Performance of the model is validated by comparison with the experimental data from a single cylinder Ricardo engine. For 60 different steady state and transient HCCI conditions, the model predicts the combustion phasing and IMEP with average errors less than 1.4 CAD and 0.2 bar respectively. A two-input two-output controller is designed to control combustion phasing and IMEP by adjusting fuel equivalence ratio and blending ratio of two Primary Reference Fuels (PRFs).

The performance of a vehicle in driving cycles can be simulated by having appropriate models for vehicle and driver. In this paper a model of an automatic driver is designed to control the speed of vehicle. The power train, having manual transmission, is modeled and a speed tracking system is designed using the fuzzy logic. Satisfactory results are obtained when the simulation results are compared with those of the experimental tests for the vehicle in the ECE driving cycle.

Homogeneous Charge Compression Ignition (HCCI) is a promising combustion concept for internal combustion engines to reduce emissions and fuel consumption. Unlike spark ignition and diesel engines in which ignition is controlled by spark and spray injection timing respectively, HCCI combustion auto-ignites given the correct mixture conditions which makes HCCI ignition difficult to control. It is thus critical to understand the characteristics of HCCI ignition timing in order to find suitable strategies for ignition control. This paper presents a modified model of ignition timing which is based on the Knock-Integral Method. Since this model doesn't require instantaneous in-cylinder parameters, it is suitable for control application on HCCI combustion. The model is tested using both simulation results of a Thermo-Kinetic Model and experimental data.

A diesel piloted natural gas engine's performance varies depending on operating conditions and has performed best under medium to high loads. It can often equal or better the fuel conversion efficiency of a diesel-only engine in this operating range. This paper presents a study performed on a multi-cylinder Cummins ISB 6.7L diesel engine converted to run stoichiometric natural gas/diesel micro-pilot combustion with a maximum diesel contribution of 10%. This study systematically quantifies and ranks the sensitivity of control factors on combustion and performance while operating at medium loads. The effects of combustion control parameters, including the pilot start of injection, pilot injection pressure, pilot injection quantity, exhaust gas recirculation, and global equivalence ratio, were tested using a design of experiments orthogonal matrix approach.