Jasim Ahmed

Electrochemical Model Based Observer Design for a Lithium-Ion Battery

Batteries are the key technology for enabling further mobile electrification and energy storage. Accurate prediction of the state of the battery is needed not only for safety reasons, but also for better utilization of the battery. In this work we present a state estimation strategy for a detailed electrochemical model of a lithium-ion battery. The benefit of using a detailed model is the additional information obtained about the battery, such as accurate estimates of the internal temperature, the state of charge within the individual electrodes, overpotential, concentration and current distribution across the electrodes, which can be utilized for safety and optimal operation. Based on physical insight, we propose an output error injection observer based on a reduced set of partial differential-algebraic equations. This reduced model has a less complex structure, while it still captures the main dynamics. The observer is extensively studied in simulations and validated in experiments for actual electric-vehicle drive cycles. Experimental results show the observer to be robust with respect to unmodeled dynamics as well as to noisy and biased voltage and current measurements. The available state estimates can be used for monitoring purposes or incorporated into a model based controller to improve the performance of the battery while guaranteeing safe operation.

Optimal charging strategies in lithium-ion battery

There is a strong need for advanced control methods in battery management systems, especially in the plug-in hybrid and electric vehicles sector, due to cost and safety issues of new high-power battery packs and high-energy cell design. Limitations in computational speed and available memory require the use of very simple battery models and basic control algorithms, which in turn result in suboptimal utilization of the battery. This work investigates the possible use of optimal control strategies for charging. We focus on the minimum time charging problem, where different constraints on internal battery states are considered. Based on features of the open-loop optimal charging solution, we propose a simple one-step predictive controller, which is shown to recover the time-optimal solution, while being feasible for real-time computations. We present simulation results suggesting a decrease in charging time by 50% compared to the conventional constant-current / constant-voltage method for lithium-ion batteries.

Modeling, estimation, and control challenges for lithium-ion batteries

Increasing demand for hybrid electric vehicles (HEV), plug-in hybrid electric vehicles (PHEV) and electric vehicles (EV) has forced battery manufacturers to consider energy storage systems that are better than contemporary lead-acid batteries. Currently, lithium-ion (Li-ion) batteries are believed to be the most promising battery system for HEV, PHEV and EV applications. However, designing a battery management system for Li-ion batteries that can guarantee safe and reliable operation is a challenge, since aging and other performance degrading mechanisms are not sufficiently well understood. As a first step to address these problems, we analyze an existing electrochemical model from the literature. Our aim is to present this model from a systems & controls perspective, and to bring forth the research challenges involved in modeling, estimation and control of Li-ion batteries. Additionally, we present a novel compact form of this model that can be used to study the Li-ion battery. We use this reformulated model to derive a simple approximated model, commonly known as the single particle model, and also identify the limitations of this approximation.

State estimation of a reduced electrochemical model of a lithium-ion battery

Batteries are the key technology for enabling further mobile electrification and energy storage. Accurate prediction of the state of the battery is needed not only for safety reasons, but also for better utilization of the battery. In this work we present a state estimation strategy for a detailed electrochemical model of a lithium-ion battery. The benefit of using a detailed model is the additional information obtained about the battery, such as accurate estimates of the state of charge within the individual electrodes, overpotential, concentration and current distribution across the electrodes, which can be utilized for safety and optimal operation. We propose an observer based on a reduced set of partial differential-algebraic equations, which are solved on a coarse spatial grid. The reduced model has a less complex structure, while still capturing the main dynamics. The observer is tested in experiments for actual electric-vehicle drive cycles. Experimental results show the observer to be robust with respect to unmodeled dynamics, as well as to noisy and biased voltage and current measurements. The available state estimates can be used for monitoring purposes, or incorporated into a model based controller to improve the performance of the battery while guaranteeing safe operation.

PDE model for thermal dynamics of a large Li-ion battery pack

Technologies for storage of electric energy are central to a range of applications-from transportation systems, including electric and hybrid vehicles, to portable electronics. Lithium-ion batteries have emerged as the most promising technology for such applications, thanks to their high energy density, lack of hysteresis, and low self-discharge currents. One of the most important problems in battery technology is achieving safe and reliable operation at low cost. Large packs of batteries, required in high-power applications such as submarines, satellites, and electric automobiles, are prone to thermal runaways which can result in damage on a large scale. Safety is typically ensured by over-design, which amounts to packaging and passive cooling techniques designed for worst-case scenarios. Both the weight and the cost of the batteries can be considerably lowered by developing models of thermal dynamics in battery packs and model-based estimators and control laws. At present, only detailed numerically-oriented models (often referred to as CFD or FEM models) exist, which are used for computationally intensive off-line tests of operating scenarios, but are unsuitable for real-time implementation. In this paper, we develop a model of the thermal dynamics in large battery packs in the form of two-dimensional partial differential equations (2D PDEs). The model is a considerable simplification of the full CFD/FEM model and therefore offers the advantage of being tractable for model-based state estimation, parameter estimation, and control design. The simulations show that our model matches the CFD model reasonably well while taking much less time to compute, which shows the viability of our approach.

Simulation of misfire and strategies for misfire recovery of gasoline HCCI

In HCCI mode with negative valve overlap, the understanding of the engine behavior in case of misfire and delayed combustion is important to provide a complete control strategy. A hybrid continuous zero dimensional model for gasoline HCCI, based on simplified chemical kinetics and a separate airflow model is introduced. CHEMKIN is used to simulate the chemical kinetics, whereas the airflow and the injection is simulated using MatLab. The model is compared to experimental data. The introduced model is used to analyze the effect of misfire and late combustions on the dynamics of the system. A state transition map is proposed to distinguish between misfire with and without recovery. Control strategies to improve the misfire recovery are suggested.

Reduced Order Modeling and Control of an Electrohydraulic Valve System

Abstract In novel combustion strategies like HCCI, fully flexible inlet and exhaust valves in terms of lift and timing are required to enable HCCI. In this paper, we explore issues related to control of an electrohydraulic variable valve system. A nonlinear model of an electrohydraulic valve system is linearized and simplified to a reduced order model to overcome numerical stability issues. A model based control algorithm is developed based on the reduced order model. The control algorithm consists of an observer to estimate the unmeasurable states and the disturbance acting on the plant, and permits tracking of any sufficiently smooth bounded trajectory. Numerical simulations and experimental results are presented for a sine wave and for a partial lift profile to indicate the effectiveness of the control algorithm developed.

Reduced-order modeling for studying and controlling misfire in four-stroke HCCI engines

It is well-known that an HCCI-based engine has a high operating efficiency and low emissions. However, the HCCI process is sensitive to disturbances that can cause the engine to misfire, especially at low loads. In this paper, we propose an efficient, physics-based model for studying engine state evolution in the presence of misfires. The model relies on a simple recursive mass balance model, simplified thermodynamic mechanisms, and use of the “integrated Arrhenius rate” with a modified threshold to model combustion phasing, occurrence of misfire, and partial burn during misfire. Simulation results for our reduced-order model, compared to a high-resolution HCCI simulation proposed in a previous work, show good match.

Novel Vehicle Stability Control Using Steer-by-Wire and Independent Four Wheel Torque Distribution

The introduction of X-By-Wire technology opens new possibilities for vehicle stability control. This technology replaces the mechanical links currently existing between the driver and different actuators with electrical connections so that the driver can be decoupled from the control system. In this paper, we consider a X-By-Wire vehicle powered by four independent wheel motors and front wheel steer-by-wire. For such a vehicle, a control algorithm is developed that employs steering and individual wheel acceleration in addition to braking to enhance stability and improve performance. Such a vehicle offers advantages in case of actuator failure where the remaining actuators can act to ensure stability and we illustrate this in simulation using our control algorithm. Finally, we describe our experimental setup and present preliminary experimental results.Copyright

Smooth switching between 2-stroke and 4-stroke modes of HCCI operation

Switching between 2-stroke and 4-stroke modes of Homogeneous Charge Compression Ignition (HCCI) operation is a promising method for extending load range of HCCI engine. Switching between the two modes introduces disturbances into the system resulting in significant tracking errors. We propose an architecture for control system and a method for calculation of control inputs which minimize the tracking errors during switching. Proposed method produces inputs for engine valve timings which insure smooth transitions between the two HCCI modes under a varying engine load. The method uses techniques from the theory of system identification and the theory of optimal control.