• Energy Research

The need for DC–DC non-inverting Buck-Boost converters is ever growing to supply tiny systems, i. e., a regulated input voltage at 3.3 V while the battery voltage can vary widely from 4.2 V down to about 2 V. Efficient power management solutions are required to extend the battery life before recharging, to successfully address line and load transients and to be cost attractive. The use of a ripple-based control loop is advocated to meet stringent dynamic performances. However, this kind of control loop is more complex to analyze and the converter still subject to bifurcations. Stable operations whatever the operating conditions, are mandatory but not straightforward to assess. Literature covers abundantly to the authors' knowledge the stability analyses of Buck converters or Boost converters but not the Buck-Boost mode. The Buck-Boost mode's stability issues are pointed out with their consequences in terms of generated Electro-Magnetic Interferences through the study of a monolithic 4-Switch Buck-Boost converter (only the L-C output filter and some of the controller's capacitors are out-of-chip). An improvement to the Sampled-Data Modeling approach for stability analysis is proposed to enable the designer to adjust adequately controller's parameters and comprehensively verify the circuit stability other than by performing repeated transient simulations. The results of this augmented method are confronted to experimental measurements on the one hand and simulation at transistor-level of the full converter on the other hand.

In hybrid vehicles, lithium-ion cells constituting a battery pack are frequently used to provide and recover high power to assist the vehicle's internal combustion engine (ICE) powertrain. This usage is more present in mild hybrid applications where the battery does not have long discharge time. Under such conditions, the pack's series resistance ${R}_{S}$ proved to be an important parameter to monitor since its evolution depends on the cell's characteristics (manufacturing tolerance, temperature, etc.). This resistance, which is monitored by the battery management system (BMS), reflecting the available power level in the cell can be used as an indicator to enhance the security of the battery pack. Its evolution can be used to quantify its aging (state of health: SoH). This paper presents an online approach to identify the cell's series resistance based on a direct estimation of ${R}_{S}$ . This parameter can be usually identified through the voltage drop occurring across the cell caused by a high current variation profile (mild hybrid conditions). These estimated values are then filtered with an “exponential moving average” method to limit the measurement noise effect. This approach provides good results for mild hybrid conditions, while minimizing the computing power required.

Due to its capacity to store or supply energy with high power, the supercapacitor is becoming an attractive component. Because of the electrostatic nature of energy storage, the endurance of this component toward repetitive charge and discharge cycles is relatively high. The goal of this paper is to demonstrate that cycling has an impact on the degradation of the supercapacitor and, as a result, on its lifetime. Based on accelerated cycling tests, some supercapacitors were studied using a dedicated test bench. Temperature, voltage, and current, which are the parameters that accelerate aging, are monitored. In fact, observations during the cycling tests show an important acceleration in the degradation compared with a similar static test having the same voltage and core temperature but without cycling. This paper proposes a method to quantify the acceleration of aging during a cycling phase.

Sliding mode control of boost converter is studied. In order to improve dynamical performances with static and dynamic specifications, we propose a systematic procedure to compute the gains of the controller based on an optimization scheme. This method is applied to the control of an energy storage system based on supercapacitors technology in order to regulate the output voltage. Given a system with large variations of input voltage and load, it is necessary to guarantee good performance of the controller for large variations of operating point. Our study shows the great influence of the controller gains on the static and dynamic performances of the system. Hence, we point out a methodology for choosing the gains.

Energy storage elements such as supercapacitors are widely used in high-power applications. However, due to single cell voltage limitation, an energy storage system with a large number of supercapacitors is often employed. Energy management systems are associated to energy storage systems in order to assure user and equipment safety. Balancing circuits, which enable the equalization of the voltage of each element in series, are a part of the energy management system device. The work presented in this paper aims to enhance the lifetime of energy storage systems. It relies on better controlling balancing circuits on the terminals of the storage system elements. With the conventional function of balancing circuit, the energy storage system is limited by its weakest element that may fail prematurely. Thus, a new balancing approach is presented, discussed, and analyzed. It is based on the elements degradation level prediction. The model predictive control used with the new approach aims to equalize aging speed between elements of a module and ensures a maximum lifetime to the energy storage system. A comparison with the conventional control shows that adopting this new approach, with the same equipment, can enhance the storage system's lifetime by dozens percent.