Adaptive Second Order Sliding Mode Control of a Fuel Cell Hybrid System for Electric Vehicle Applications

Abstract

We present an adaptive-gain second order sliding mode (SOSM) control applied to a hybrid power system for electric vehicle applications. The main advantage of the adaptive SOSM is that it does not require the upper bound of the uncertainty. The proposed hybrid system consists of a polymer electrolyte membrane fuel cell (PEMFC) with a unidirectional DC/DC converter and a Li-ion battery stack with a bidirectional DC/DC converter, where the PEMFC is employed as the primary energy source and the battery is employed as the second energy source. One of the main limitations of the FC is its slow dynamics mainly due to the air-feed system and fuel-delivery system. Fuel starvation phenomenon will occur during fast load demand. Therefore, the second energy source is required to assist the main source to improve system perofrmance. The proposed energy management system contains two cascade control structures, which are used to regulate the fuel cell and battery currents to track the given reference currents and stabilize the DC bus voltage while satisfying the physical limitations. The proposed control strategy is evaluated for two real driving cycles, that is, Urban Dynamometer Driving Schedule (UDDS) and Highway Fuel Economy Driving Schedule (HWFET).

Control of a Charger/Discharger DC/DC Converter with Improved Disturbance Rejection for Bus Regulation

“…A widely used battery charger/discharger DC/DC converter is presented in Figure 2, which is based on a bidirectional boost (buck) converter [38]. Moreover, this figure also illustrates a classical cascade current-voltage control structure, in which the current controller acts on the MOSFET signal u directly (e.g., sliding-mode, peak current, valley current controllers) or using a PWM (e.g., average current control).…”

“…The cascade structure has also been used to control the power flow between the battery and the DC bus. This case was reported in [38], which uses an inner control loop to regulate the battery current and an outer control loop to regulate the DC bus energy. Note that the circuit presented in Figure 2 has an equivalent behavior: in a power system with a regulated DC bus, similar to the one presented in Figure 1, the difference between the load power and power provided by the main generator is stored/supplied in the DC bus capacitor.…”

“…To study the dynamic behavior of the closed-loop system depending on the type of damping ratio, G dc (s) is rewritten as shown in (37), where ω n represents the natural frequency of the system. To exclusively analyze the effect of the damping ratio, the transfer function is normalized in terms of the natural frequency using the normalized Laplace variable s N = s ω n as in (38). Figure 7 shows the normalized dynamic response of G dc (s) to a step perturbation for different damping ratios: the higher the damping ratio is, the lower is the maximum overshoot.…”

Advanced passivity-based, aging-tolerant control for a fuel cell/super-capacitor hybrid system

“…One more element is sometimes added, such as a battery [11,12,13,14,15,16] or a wind turbine [17,18] for microgrid applications [19]. Fuzzy logic, passivity-based control [6,20,21,22], flatness based control [23], Lure-Lyapunov theory [24], Lyapunov-based nonlinear control [25,26], adaptive second order sliding mode control [27], adaptive control [28], Model Predictive Control (MPC) [13], regular controllers or optimization algorithms [29] are typically used in the controller design of such systems. These controllers are based on the same principle, i.e.…”

Adaptive Second-Order Sliding Mode Control Design for a Class of Nonlinear Systems with Unknown Input

“…However, such approach constrains the sliding system's trajectories not to the sliding surface but to its vicinity losing the robustness to the disturbances. Higher order sliding mode control techniques are used in [29][30][31][32] which allow driving the sliding variable and its consecutive derivatives to zero in the presence of the disturbances. However, the main challenge of high order sliding mode controllers is the use of high order time derivatives of sliding variable.…”