Sensorless estimation of pressure head and flow of a continuous flow artificial heart based on input power and rotational speed.

The present study has proposed a new method for estimating the pressure head (P(t)[mm Hg]) and flow (Q(t)[L/min]) of a centrifugal pump on the basis of voltage (V(t)[V]), current (I(t)[A]), and rotational speed (N(t)[k(rpm)]) of the DC motor for a pump without any additional sensors. In the proposed estimation method, two auto-regressive exogenous (ARX) models are employed. One ARX model has an output, P(t) or Q(t), and three inputs, VI(t) = V(t)I(t) and N(t) and the steady state gain (K) of the system from VI(t) to N(t). It can be assumed that K may include the information on viscosity of blood. The coefficient parameters of this ARX model are identified in an off-line fashion before implantation of the pump. After implantation, P(t) or Q(t) is estimated by the same ARX model with the already identified parameters. The other ARX model is used to identify Kon the basis of VI(t) and N(t) in an on-line fashion every time the viscosity of blood may change. In the experiment, a mock circulatory system consisting of a centrifugal pump and a reservoir with 37% glycerin or water was employed. The root mean square error between measured Q(t) and its estimate obtained from the proposed method was 1.66L/min. On the other hand, a different method based on a single ARX model with inputs of VI(t) and N(t), but without the additional input of K, yielded the corresponding estimation error of 2.22L/min. This means that the proposed method can reduce its estimation error by about 25% in comparison with a method that cannot cope with the change in blood viscosity.