The centrifugal blood pump is a commonly used ventricular assist device. It can replace part of the heart function, pumping blood throughout the body in order to maintain normal function. However, the high shear stress caused by the impeller rotating at high speeds can lead to hemolysis and, as a consequence, to stroke and other syndromes. Therefore, reducing the hemolysis level while ensuring adequate pressure generation is key to the optimization of centrifugal blood pumps. In this study, a screw centrifugal blood pump was used as the research object. In addition, pressure generation and the hemolysis level were optimized simultaneously using a coupled algorithm composed of random forest (RF) and multi-objective gray wolf optimization (MOGWO). After verifying the prediction accuracy of the algorithm, three optimized models were selected and compared with the baseline model in terms of pressure cloud, 2D streamline, SSS distribution, HI distribution, and vortex distribution. Finally, via a comprehensive evaluation, the optimized model was selected as the final optimization design, in which the pressure generation increased by 24% and the hemolysis value decreased by 48%.

In this paper, the cavitation characteristics of centrifugal blood pumps under variable speeds were studied by using ANSYS-CFX and MATLAB software. The study proposed a multi-scale model of the “centrifugal blood pump—left heart blood circulation”, and analyzed the cavitation characteristics of the centrifugal blood pump. The results showed that the cavitation in the impeller first appeared near the hub at the inlet of the impeller. As the inlet pressure decreased, the cavitation gradually strengthened and the bubbles gradually developed in the outlet of the impeller. The cavitation intensity increased with the increase of impeller speed. The curve of the variable speeds of the centrifugal blood pump in the optimal auxiliary state was obtained, which could effectively improve the aortic pressure and flow. In variable speeds, due to the high aortic flow and pressure during the ejection period, the sharp increases in speeds led to cavitation. The results could provide a guidance for the optimal design of the centrifugal blood pump.

Based on the nonlinear relationship between heart rate and stroke volume, a flow model of left ventricular circulation was improved, and a variable-speed blood-pump control strategy based on heart-rate feedback was proposed. The control strategy was implemented on a system combining the rotary blood pump and blood circulation models of heart failure. The aortic flow of a healthy heart at different heart rates was the desired control goal. Changes in heart rate were monitored and pump speed was adjusted so that the output flow and aortic pressure of the system would match a normal heart in real time to achieve the best auxiliary state. After simulation with MATLAB, the cardiac output satisfied the ideal perfusion requirements at different heart rates, and aortic pressure demonstrated lifting and had good pulsatile performance when a variable-speed blood pump was used. The coupled model reflected the relationship between hemodynamic parameters at different heart rates with the use of the variable-speed blood pump, providing a theoretical basis for the blood-pump-assisted treatment of heart failure and the design of physiological control strategies.

Introduction: Traditional percutaneous ventricular assist devices (PVADs) face limitations due to their small implantation size, requiring higher rotational speeds to meet left ventricular support demands. However, the elevated shear stress induced by high-speed operation leads to excessive hemolysis, necessitating design improvements for better clinical applicability. Method: This study presents a foldable implantable blood pump featuring a collapsible flexible impeller and pump casing, which reduces its profile during implantation and expands to operational size at the target position, thereby allowing lower rotational speeds and improved hemolytic performance. Through numerical simulations combined with response surface methodology (RSM), we systematically analyzed the influence of various structural parameters on pump head and hemolysis index (HI), aiming at parametric optimization of the initial model for enhanced hydraulic efficiency and reduced blood trauma risk. Results: Simulation analysis of seven parameter configurations identified five key structural parameters with dominant effects on head and HI: impeller inlet angle, impeller outlet angle, diffuser inlet angle, diffuser wrap angle, and impeller-diffuser gap. Using Box-Behnken Design (BBD), we established dual-response prediction models for both head and HI, analyzed significant interaction terms, and derived an optimized configuration achieving a 6.9% increase in head pressure and 17.9% reduction in HI compared to the initial design. Additional analysis revealed that increasing tip clearance reduces hemolysis at the cost of moderate head decrease. Conclusion: We designed and optimized a foldable axial-flow blood pump for transaortic implantation. The optimized configuration demonstrates a 6.9% head improvement to 2.346 m and 17.9% HI reduction to 1.081 × 1 0 − 2 % . Furthermore, increasing tip clearance from 0.2 mm to 0.4 mm provides additional hemolysis reduction without excessively compromising the pressure head.

This study focuses on a blood pump system equipped with four radial active magnetic bearings (RAMBs). The finite element method (FEM) was employed to optimize the physical parameters of the system. Based on this optimization, two intelligent PID tuning strategies—particle swarm optimization (PSO) and backpropagation (BP) neural networks—were compared. First, a differential control model of a single-degree-of-freedom active magnetic bearing was developed, based on the topology and operating principles of the radial magnetic bearings. Then, magnetic circuit parameters were precisely identified through finite element simulation, enabling accurate optimization of the physical model. To enhance control accuracy, intelligent tuning strategies based on PSO and BP neural networks were applied, effectively addressing the limitations of conventional PID controllers, which often rely on empirical tuning and lack precision. Finally, simulation experiments were conducted to evaluate the optimization performance of PSO and BP neural networks in the magnetic bearing control system. The results demonstrate that the improved PSO algorithm offers significant advantages over both the BP neural network and traditional manual PID tuning. Specifically, it achieved a rise time of 0.0049 s, a settling time of 0.0079 s, and a steady-state error of 0.0013 mm. The improved PSO algorithm ensures system stability while delivering faster dynamic response and superior control accuracy.

Implanting rotary blood pumps (RBPs) has become the principal treatment for patients suffering from severe heart failure. There are still many challenges to address for RBP control systems. These problems include meeting the patient’s physiological perfusion, eliminating postoperative complications, as well as debugging the patient’s physiological control system (automatically and indiscriminately). This paper proposes a non-invasive adaptive control system based on the Frank–Starling-like mechanism (NAC-FSL) to solve these problems. This control system uses the motor speed of the rotary blood pump as the only input variable, and the pump flow was estimated by the motor speed for achieving non-invasive detection. Simultaneously, a cardiovascular reference model was developed to provide an appropriate real-time preload for heart failure patients. The Frank–Starling-like control baseline was tracked to obtain the desired reference average pump flow by using the preload. Avoiding suction was done by adopting the control baseline (CLn), which included a flat slope under a high preload. Moreover, the NAC-FSL system could potentially unload the left ventricle and provide a higher pump flow with a smaller error during the exercise state, as compared to the CSC system. Finally, the K value indicating the preload sensitivity in the NAC-FSL controller was optimized to meet the perfusion needs according to the hemodynamic parameters.