Low Complexity Model Predictive Control of a Diesel Engine Airpath.

The diesel air path (DAP) system has been traditionally challenging to control due to its highly coupled nonlinear behavior and the need for constraints to be considered for driveability and emissions. An advanced control technology, model predictive control (MPC), has been viewed as a way to handle these challenges, however, current MPC strategies for the DAP are still limited due to the very limited computational resources in engine control units (ECU). A low complexity MPC controller for the DAP system is developed in this dissertation where, by "low complexity," it is meant that the MPC controller achieves tracking and constraint enforcement objectives and can be executed on a modern ECU within 200 microseconds, a computation budget set by Toyota Motor Corporation. First, an explicit MPC design is developed for the DAP. Compared to previous explicit MPC examples for the DAP, a significant reduction in computational complexity is achieved. This complexity reduction is accomplished through, first, a novel strategy of intermittent constraint enforcement. Then, through a novel strategy of gain scheduling explicit MPC, the memory usage of the controller is further reduced and closed-loop tracking performance is improved. Finally, a robust version of the MPC design is developed which is able to enforce constraints in the presence of disturbances without a significant increase in computational complexity compared to non-robust MPC. The ability of the controller to track set-points and enforce constraints is demonstrated in both simulations and experiments. A number of theoretical results pertaining to the gain scheduling strategy is also developed. Second, a nonlinear MPC (NMPC) strategy for the DAP is developed. Through various innovations, a NMPC controller for the DAP is constructed that is not necessarily any more computationally complex than linear explicit MPC and is characterized by a very streamlined process for implementation and calibration. A significant reduction in computational complexity is achieved through the novel combination of Kantorovich's method and constrained NMPC. Zero-offset steady state tracking is achieved through a novel NMPC problem formulation, rate-based NMPC. A comparison of various NMPC strategies and developments is presented illustrating how a low complexity NMPC strategy can be achieved.PhDAerospace EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/120832/1/huxuli_1.pd

Variable Geometry Turbocharger Technologies for Exhaust Energy Recovery and Boosting-A Review

As emissions regulations become increasingly demanding, higher power density engine (downsized/downspeeded and increasingly right-sized) requirements are driving the development of turbocharging systems. Variable geometry turbocharging (VGT) at its most basic level is the first step up from standard fixed geometry turbocharger systems. Currently, VGTs offer significant alternative options or complementarity vis-à-vis more advanced turbocharging options. This review details the range of prominent variable geometry technologies that are commercially available or openly under development, for both turbines and compressors and discusses the relative merits of each. Along with prominent diesel-engine boosting systems, attention is given to the control schemes employed and the actuation systems required to operate variable geometry devices, and the specific challenges associated with turbines designed for gasoline engines

Flexible and robust control of heavy duty diesel engine airpath using data driven disturbance observers and GPR models

Diesel engine airpath control is crucial for modern engine development due to increasingly stringent emission regulations. This thesis aims to develop and validate a exible and robust control approach to this problem for speci cally heavy-duty engines. It focuses on estimation and control algorithms that are implementable to the current and next generation commercial electronic control units (ECU). To this end, targeting the control units in service, a data driven disturbance observer (DOB) is developed and applied for mass air ow (MAF) and manifold absolute pressure (MAP) tracking control via exhaust gas recirculation (EGR) valve and variable geometry turbine (VGT) vane. Its performance bene ts are demonstrated on the physical engine model for concept evaluation. The proposed DOB integrated with a discrete-time sliding mode controller is applied to the serial level engine control unit. Real engine performance is validated with the legal emission test cycle (WHTC - World Harmonized Transient Cycle) for heavy-duty engines and comparison with a commercially available controller is performed, and far better tracking results are obtained. Further studies are conducted in order to utilize capabilities of the next generation control units. Gaussian process regression (GPR) models are popular in automotive industry especially for emissions modeling but have not found widespread applications in airpath control yet. This thesis presents a GPR modeling of diesel engine airpath components as well as controller designs and their applications based on the developed models. Proposed GPR based feedforward and feedback controllers are validated with available physical engine models and the results have been very promisin

Model predictive emissions control of a diesel engine airpath: Design and experimental evaluation

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/163480/2/rnc5188.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/163480/1/rnc5188_am.pd

Model-based control of a turbocharged diesel engine with high- and low-pressure exhaust gas recirculation

Modern Diesel engines fulfil challenging requirements for emission limits, fuel consumption and ride comfort by numerous modular combinable components and mechatronical actuators. These components are utilised for precondition and aftertreatment of air, fuel and exhaust gas, which is involved in the combustion process. In this dissertation a methodology for a model-based function development with semi-physical engine models for control of air path quantities of an exemplary Diesel engine with high-pressure (HP-EGR) and low-pressure exhaust gas recirculation (LP-EGR) is developed. In this framework for function development black-box models for stationary and dynamical emission formation are utilised to optimise reference values for the air path control and to rate the developed control scheme with regard to the cumulated driving cycle emissions of the new European driving cycle (NEDC). A combination of HP-EGR and LP-EGR represents a novel approach to significantly lower the particulate and NOx emissions of Diesel engines. A semi-physical mean value engine model with lumped parameters is the base to analyse the system properties of the complex air path. In doing so, the additional LP-EGR shows only minor influences to the quantities charge air pressure and HP-EGR, while there are significant influences of these quantities on the LP-EGR mass flow rate. Furthermore, the LP-EGR is characterised by significant gas propagation times in the intake and exhaust system. These delays are modelled by a gas composition model, which is incorporated into the control scheme. NOx and particulate emissions as well as engine torque are stationary modelled by local polynomial models with input quantities of the combustion process. These quantities are air mass flow rate, charge air pressure, intake temperature and crank angle of 50% mass fraction burned. A bilinear interpolation between engine speed and injection quantity transforms local polynomial models into global models. Models for the dynamical emission formation are given by considering the combustion as a batch process. Consequently all dynamics are included in the quantities of the cylinder charge at intake valve closing and the emission measurement dynamics. Thus, a combination of a dynamical gas composition model, stationary emission models and models for the emission measurement dynamics yield the dynamical course of the engine emissions. The investigated system properties and the emission models deliver the control variables charge air pressure, air content and intake temperature for the engine with VGT-turbocharger, HP- and LP-EGR. A stationary optimisation with regard to emissions and engine torque delivers reference values for the air path control and further shows the potential of the LP-EGR to lower the emissions. Due to the multi-variable characteristics of the air path with different dynamics, there are increased dynamical emissions at engine transients. These dynamical emissions are lowered by dynamical optimised reference values for the air path control. Generally, the air path is a strongly nonlinear process and the multitude of engine variants and engine operation modes result in a trade-off between achievable control quality, control robustness and number of control parameter sets. A semi-physical feedforward control, which is based upon parameterised model relationships of the mean value engine model delivers a good response to setpoint changes. Thus, the disturbance rejection can be achieved by relatively simple controllers. This results in an significantly lower application effort of control parameters and allows by its modular structure to exchange engine components without the drawback to completely re-parameterise the control parameters. A reference value transformation with modelled states of the gas composition model compensates long gas propagation times in the intake and exhaust system and delivers an optimal air content in the cylinder charge. All control concepts are validated with measurements at the engine test bench. Finally, the derived control concepts for the LP-EGR are compared to the classical HP-EGR control with regard to the cumulated driving cycle emissions. In this investigation the proportion of stationary and dynamical emissions is clearly quantified. In a nutshell this dissertation is an important contribution for model-based optimisation and function development for the air path control of Diesel engines. The given combination of models for dynamical emission formation, dynamically optimised reference values for the air path control and semi-physical control design are a holistic framework to master the complexity and variance of future Diesel and gasoline engines

Control-oriented modeling, validation, and analysis of a natural gas engine architecture

In order to improve performance and meet increasingly tight emissions regulations, engine manufacturers must improve algorithms used to control the engine. One possible strategy is to utilize centralized control algorithms that take into account the coupled interactions between inputs and outputs. Implementing a centralized control strategy often requires some kind of dynamic model of the system, which is a primary motivation for modeling efforts in this thesis. In a methodical fashion, this thesis derives a control model for a natural gas engine architecture and validates this control model against reference data in simulation. Additionally, this thesis performs control-oriented analysis on a state-space model provided by Caterpillar to determine the engine’s suitability to decentralized control. Based on the results of the control-oriented analysis, the thesis demonstrates how a decentralized control framework can be implemented. The first study declares a set of seven state variables that characterize the operation of the engine. The engine of interest runs on natural gas and is used in power generation applications. Additionally, this study models all mass flow rates and power terms as functions of the selected state variables. These models are then validated against truth-reference data. This study also explicitly states the assumptions and simplifications that correspond to each of the models. The second study derives dynamic equations for each of the seven state variables via a first-principles approach. The dynamic state equations contain expressions for mass flow rates and power that were modeled in the first study. This study then numerically validates the entire state-space model by exercising control inputs from reference data on it. Together, the seven state equations effectively serve as a control model that can be used for controller synthesis. The goal of the first two studies is to demonstrate a procedure for obtaining a control model for an engine architecture, not to obtain a high-fidelity simulation model. The third study demonstrates control-oriented analysis on a state-space model provided by Caterpillar. The relative gain array (RGA) is used to show that the system is well-suited is for decentralized control. This study implements a decentralized control structure on the state-space model provided by Caterpillar and validates, in simulation, its ability to achieve reference tracking for desired outputs

Model Predictive Control of Modern High-Degree-of-Freedom Turbocharged Spark Ignited Engines with External Cooled EGR

The efficiency of modern downsized SI engines has been significantly improved using cooled Low-Pressure Exhaust Gas Recirculation, Turbocharging and Variable Valve Timing actuation. Control of these sub-systems is challenging due to their inter-dependence and the increased number of actuators associated with engine control. Much research has been done on developing algorithms which improve the transient turbocharged engine response without affecting fuel-economy. With the addition of newer technologies like external cooled EGR the control complexity has increased exponentially. This research proposes a methodology to evaluate the ability of a Model Predictive Controller to coordinate engine and air-path actuators simultaneously. A semi-physical engine model has been developed and analyzed for non-linearity. The computational burden of implementing this control law has been addressed by utilizing a semi-physical engine system model and basic analytical differentiation. The resulting linearization process requires less than 10% of the time required for widely used numerical linearization approach. Based on this approach a Nonlinear MPC-Quadratic Program has been formulated and solved with preliminary validation applied to a 1D Engine model followed by implementation on an experimental rapid prototyping control system. The MPC based control demonstrates the ability to co-ordinate different engine and air-path actuators simultaneously for torque-tracking with minimal constraint violation. Avenues for further improvement have been identified and discussed

Observability studies of a turbocharger systems

The use of diesel engine turbochargers is increasing today, as it represents an option that o ers high e ciency and low fuel consumption. To design the control system in order to reduce the level of exhaust emissions there is a need for information about all states that are not measurable. To this end, observers or virtual sensors are more frequently applied, achieving estimates of the system states from inputs and measured output. To propose an observer, the precise mathematical model of the air path diesel engine system is used. This is a nonlinear model of a third order which is analyzed in terms of observability. From the point of view of systems theory, certain conditions and the existence of a transformation of the system state, called di eomorphism, need to be evaluated. Observers have been designed based on di erent approaches: Extended Luenberger Observers, High Gain Observers, Sliding Modes Observers and Extended Kalman-Bucy Filters. They have been validated by simulation for the system under consideration in this work.Tesi