Vehicle-Vehicle Energy Interaction Converter of Electric Vehicles: A Disturbance Observer Based Sliding Mode Control Algorithm

Abstract

The electric vehicle technology is one of the most promising candidates to reduce fuel consumption and <inline-formula><tex-math notation="LaTeX">$\rm CO_2$</tex-math></inline-formula> emission. Although electric vehicles have been widely promoted by governments around the world, their development is seriously hampered due to charger unavailability and range anxiety. Based on this, this paper designs an energy interaction converter between two electric vehicles, which is controlled through disturbance observer based sliding mode control algorithm. For this converter, three main demands should be satisfied, i.e., high power density, weak source and constant power load. Therein, weak source whose minimum short circuit ratio (SCR) belongs to Jia <i>et al.</i>, 2020 and Wang <i>et al.</i>, 2020, is always called weak grid. Firstly, the equivalent impedance switching process is introduced to eliminate the impact of weak source. Meanwhile, the equivalent six channel interleaved floating dual boost converter is chosen to satisfy the high power density demand, whose generalized state-space function is further built to provide an indispensable preprocessing for following controller design. Moreover, in order to solve the problem regarding low frequency/sub-synchronous oscillation caused through constant power load feature regarding the energy consumption vehicle and weak source feature regarding the energy supply vehicle, a disturbance observer based sliding mode control algorithm is proposed through using generalized state-space function to provide standard DC power with both constant voltage and power. Furthermore, the proportional-resonant controller is proposed to solve the current sharing problem among six parallel channels, which reduces the heat loss and improves the service life of the device. Finally, simulation and experimental results verify the high performance of the proposed control algorithm.