The traditional model predictive control(MPC)strategy requires an accurate time-domain model of the power converter

but the multi-port converter has complex control variables

power coupling

and high-order model

making it difficult to obtain the analytical solution expression for the optimal predictive control variable. Moreover

traditional model predictive control suffers from high sensitivity to sampling noise. A continuous control set simplified model predictive control(SMPC)method was proposed based on Kalman filter and a simple noise tolerance strategy

which reduces complexity of the predictive model

and achieves fast dynamic response and wide noise tolerance range of series resonant multi-active-bridge(SR-MAB)converters. Firstly

the fundamental harmonic analysis method was used to calculate the transmission power of the SR-MAB converter and feasibility of this method was verified; Secondly

a linear simplified predictive model was established according to the classification of ports types

and the simplified model parameters were calibrated through Kalman filter algorithm; Finally

to address the issue of high sensitivity to noise

a simple and efficient noise tolerance enhancement strategy was designed by redefining the correlation coefficients of the simplified model

expanding the noise tolerance range

and balancing dynamic performance

system cost

and computational burden. The experimental results show that compared to PI control

the system's dynamic response time is reduced effectively under SMPC strategy without significantly increasing the computational burden on the processor. The proposed noise tolerance method effectively reduces the resonant current stress at each port.