Reduced-order estimation and optimisation of claw-shaped throttling notch via CFD analysis, surrogate models, and CCMO algorithm

The non-road mobile machinery such as loaders are in immediate requirement for energy conservation. In non-road mobile machinery, the hydraulic spool valve serves as a critical component. Under conditions of high pressure and substantial flow rates, particularly with the presence of high-order throttling notches, this valve experiences significant pressure drop across its port. This phenomenon leads to substantial energy loss from the pump. Currently, there is a scarcity of research examining the interplay between the structure of high-order notches and pressure drop. This gap poses difficulties in the development of efficient notch-matching designs. In this article, a coevolutionary constrained multi-objective optimisation (CCMO) approach based on the novel reduced-order discharge area surrogate model (RO-DASM) and computational fluid dynamics (CFD) analysis for the coupled claw-shaped notch (CSN) hydraulic spool valve is proposed. At first, the RO-DASM is built to decouple multiparameter CSN flow rate-pressure drop (FR-PD) estimation into five simplified K-shaped notch (KSN) FR-PD estimations comparing four surrogate models. Thereafter, the RO-DASM and the CCMO algorithm are integrated for the CSN spool optimisation based on the CFD numerical simulation. Finally, the optimisation efficiency is verified by the experiment. Results demonstrate that the presented RO-DASM model realises a reliable prediction for pressure drop, whose average deviation is below 5% compared to CFD simulation under the flow rate of 250, 350, and 450 L/min. The pressure drop of the CSN valve port reduces by as much as 13.7% after optimisation. The suggested framework can strengthen the CSN hydraulic spool valve optimisation efficiency and can be performed to diverse kinds of high-order notches flexibly.