Anna G. Stefanopoulou

Control of fuel cell breathing

In this article we analyzed and designed air flow controllers that protect the fuel cell (FC) stack from oxygen starvation during step changes of current demand. The steady-state regulation of the oxygen excess ratio in the FCS cathode achieved by assigning an integrator to the compressor flow. Linear observability techniques were employed to demonstrate improvements in transient oxygen regulation when the FCS voltage is included as a measurement for the feedback controller. The FCS voltage signal contains high frequency information about the FC oxygen utilization, and thus, is a natural and valuable output for feedback. We used linear optimal control design to identify the frequencies at which there is a severe tradeoff between the transient system net power performance and the stack starvation control. The limitation arises when the FCS system architecture dictates that all auxiliary equipment is powered directly from the FC with no secondary power sources. This plant configuration is preferred due to its simplicity, compactness, and low cost. The FCS impedance given the closed-loop air flow and perfect humidification and temperature regulation captures the FC current-voltage dynamic relationship. It is expected that the closed-loop FCS impedance will provide the basis for the systematic design of FC stack electronic components.

Control-oriented modeling and analysis for automotive fuel cell systems

Fuel Cells are electrochemical devices that convert the chemical energy of a gaseous fuel directly into electricity. They are widely regarded as a potential future stationary and mobile power source. The response of a fuel cell system depends on the air and hydrogen feed, flow and pressure regulation, and heat and water management. In this paper, we develop a dynamic model suitable for the control study of fuel cell systems. The transient phenomena captured in the model include the flow and inertia dynamics of the compressor, the manifold filling dynamics (both anode and cathode), reactant partial pressures, and membrane humidity. It is important to note, however, that the fuel cell stack temperature is treated as a parameter rather than a state variable of this model because of its long time constant. Limitations and several possible applications of this model are presented.

Recursive least squares with forgetting for online estimation of vehicle mass and road grade: theory and experiments

Good estimates of vehicle mass and road grade are important in automation of heavy duty vehicles, vehicle following manoeuvres or traditional powertrain control schemes. Recursive least square (RLS) with multiple forgetting factors accounts for different rates of change for different parameters and thus, enables simultaneous estimation of the time-varying grade and the piece-wise constant mass. An ad hoc modification of the update law for the gain in the RLS scheme is proposed and used in simulation and experiments. We demonstrate that the proposed scheme estimates mass within 5% of its actual value and tracks grade with good accuracy provided that inputs are persistently exciting. The experimental setups, signals, their source and their accuracy are discussed. Issues like lack of persistent excitations in certain parts of the run or difficulties of parameter tracking during gear shift are explained and suggestions to bypass these problems are made.

Control of variable geometry turbocharged diesel engines for reduced emissions

The emission control problem for an automotive direct injected compression ignition (diesel) engine equipped with exhaust gas recirculation (EGR) and a variable geometry turbocharger (VGT) is considered. The objective is to operate the engine to meet drivers torque demand and minimize NO/sub x/ emissions while at the same time avoiding visible smoke generation. It is demonstrated that the steady-state optimization of engine emissions results in operating points where EGR and VGT actuators are in effect redundant in their effect on the variables that most directly affect the emissions. A multivariable feedback controller is proposed which accounts for this actuator redundancy. Furthermore, it coordinates the two actuators to fully utilize their joint effect on engine emission performance. Experimental results confirm good response properties of the proposed controller.

Modeling and control for PEM fuel cell stack system

A nonlinear fuel cell system dynamic model that is suitable for control study is presented. The transient phenomena captured in the model include the flow characteristics and inertia dynamics of the compressor, the manifold filling dynamics, and consequently, the reactant partial pressures. Characterization of the fuel cell polarization curves based on time varying current, partial oxygen and hydrogen pressures, temperature, membrane hydration allows analysis and simulation of the transient fuel cell power generation. An observer based feedback and feedforward controller that manages the tradeoff between reduction of parasitic losses and fast fuel cell net power response during rapid current (load) demands is designed.

Current Management in a Hybrid Fuel Cell Power System: A Model-Predictive Control Approach

The problem of oxygen starvation in fuel cells coupled with air compressor saturation limits, is addressed in this paper. We propose using a hybrid configuration, in which a bank of ultracapacitors supplements the polymer electrolyte membrane fuel cell during fast current transients. Our objective is to avoid fuel cell oxygen starvation, prevent air compressor surge and choke, and simultaneously match an arbitrary level of current demand. We formulate the distribution of current demand between the fuel cell and the bank of ultracapacitors in a model predictive control framework, which can handle multiple constraints of the hybrid system. Simulation results show that reactant deficit during sudden increase in stack current is reduced from 50% in stand-alone architecture to less than 1% in the hybrid configuration. In addition, the explicit constraint handling capability of the current management scheme prevents compressor surge and choke and maintains the state-of-charge of the ultracapacitor within feasible bounds

EGR-VGT control schemes: experimental comparison for a high-speed diesel engine

Variable-geometry turbochargers (VGTs) are employed in high-end diesel engines. These VGTs also help in controlling the trade-offs in emissions performance. Exhaust gas recirculation (EGR) is used to dilute the combustion mixture, resulting in lower peak combustion temperatures and a lower oxygen concentration and hence lower NOx emissions. In this article, we compare some of the control methodologies previously presented and some not yet presented to evaluate their benefits experimentally. We do not include any new theory. Rather we refer to other sources for the development of the controllers evaluated. We present an objective comparison of advanced control methodologies on a complex industrial problem with widespread applications. The control methodologies discussed are essentially system based, i.e., the initial controller is developed on an engine model.

Lithium-Ion Battery State of Charge and Critical Surface Charge Estimation Using an Electrochemical Model-Based Extended Kalman Filter

This paper presents a numerical calculation of the evolution of the spatially resolved solid concentration in the two electrodes of a lithium-ion cell. The microscopic solid concentration is driven by the macroscopic Butler–Volmer current density distribution, which is consequently driven by the applied current through the boundary conditions. The resulting, mostly causal, implementation of the algebraic differential equations that describe the battery electrochemical principles, even after assuming fixed electrolyte concentration, is of high order and complexity and is denoted as the full order model. The full order model is compared with the results in the works of Smith and Wang (2006, “Solid-State Diffusion Limitations on Pulse Operation of a Lithium-Ion Cell for Hybrid Electric Vehicles,” J. Power Sources, 161, pp. 628–639) and Wang et al. (2007 “Control oriented 1D Electrochemical Model of Lithium Ion Battery,” Energy Convers. Manage., 48, pp. 2565–2578) and creates our baseline model, which will be further simplified for charge estimation. We then propose a low order extended Kalman filter for the estimation of the average-electrode charge similarly to the single-particle charge estimation in the work of White and Santhanagopalan (2006, “Online Estimation of the State of Charge of a Lithium Ion Cell,” J. Power Sources, 161, pp. 1346–1355) with the following two substantial enhancements. First, we estimate the average-electrode, or single-particle, solid-electrolyte surface concentration, called critical surface charge in addition to the more traditional bulk concentration called state of charge. Moreover, we avoid the weakly observable conditions associated with estimating both electrode concentrations by recognizing that the measured cell voltage depends on the difference, and not the absolute value, of the two electrode open circuit voltages. The estimation results of the reduced, single, averaged electrode model are compared with the full order model simulation. DOI: 10.1115/1.4002475

Extremum seeking control for soft landing of an electromechanical valve actuator

Many electromagnetic actuators suffer from high velocity impacts. One such actuator is the electromechanical valve actuator, recently receiving attention for enabling variable valve timing in internal combustion engines. Impacts experienced by the actuator are excessively loud and create unnecessary wear. This paper presents an extremum seeking controller designed to reduce the magnitude of these impacts. Based on a measure of the sound intensity at impact, the controller tunes a nonlinear feedback to achieve impact velocities of less than 0.1m/s while maintaining transition times of less than 4.0ms. The control strategy is implemented with an eddy current sensor, to measure the valve position, and a microphone.

Lithium-ion battery state of charge estimation with a Kalman Filter based on a electrochemical model

Lithium-ion battery is the core of new plug-in hybrid-electrical vehicles (PHEV) as well as considered in many 2nd generation hybrid electric vehicles (HEV). In most cases the lithium-ion battery performance plays an important role for the energy management of these vehicles as high-rate transient power source cycling around a relatively fixed state of charge (SOC). In this paper an averaged electrochemical Lithium-ion battery model suitable for estimation is presented. The model is based on an averaged approximated relationship between (i) the Butler-Volmer current and the solid concentration at the interface with the electrolyte and (ii) the battery current and voltage. A 4th order model based extended Kalman filter (EKF) is then designed and the estimation results are tested in simulation with the non-averaged model.