Electro-hydraulic servo pump-controlled systems have advantages such as energy saving and high integration and are widely applied in aerospace, engineering machinery, and other fields. However, the input and state delays introduced by drive circuit, control period, and oil leakage result in lower dynamic response speed compared to traditional valve control systems, which restricts the promotion of the system. In this paper, a prescribed performance trajectory tracking control method is proposed to improve the transient and steady-state performance of the system. A performance function is designed to constrain the range of trajectory tracking errors. The constrained space is mapped to an unconstrained space via a homeomorphic transformation, and the control laws are designed by integrating it with the backstepping method. In the final step of the backstepping design, the input and state delays are processed using Lyapunov–Krasovskii functionals. The simulation and experimental results show that under the condition of fixed input delay and state delay, the trajectory tracking errors converge within the preset range, and all states of the system are uniformly bounded. The results demonstrate the effectiveness of the proposed method in this paper.

As the ‘heart’ of energy vehicles, the lithium-ion battery is in desperate need of precision improvement, green production, and cost reduction. To achieve this goal, the electro-hydraulic servo pump control system (EHSPCS) is applied to the lithium-ion battery pole rolling mill (LBPRM). However, this development can lead to limited dynamic performance and large power loss as a result of the EHSPCS unique volume direct-drive control mode. At present, how to solve this conflict has not been studied and how the EHSPCS component parameters influence the dynamic response, power loss, and economic performance is not clear. In this paper, a multi-objective optimization (MOO) model for the LBPRM-EHSPCS is proposed by comprehensively considering the dynamic, efficiency, and economic characteristics. Firstly, the evaluation model of the dynamic response, power loss, and cost is investigated. Then, the NSGA-II algorithm is introduced to address the Pareto front of the MOO model. Finally, the power loss and dynamic response of the LBPRM-EHSPCS before and after optimization are tested to validate the viability of the raised method. Results indicate that power loss is decreased by as much as 7.2% while steady-state precision is greatly improved after optimization. The proposed framework enhances the performance in lithium-ion battery manufacturing and can be applied to other kinds of hydraulic systems.

Facing the development trend of electrification of construction machinery, in view of the drawbacks of the existing electro-hydraulic-load-sensitive system in terms of dynamic characteristics and usage of energy, based on the drive source of a servo motor-driven quantitative pump, an electro-hydraulic-load-sensitive system on the basis of torque open-loop control was proposed. Firstly, the working principle of the system was introduced and the system’s operating characteristics and energy consumption characteristics were theoretically analyzed. Secondly, in order to balance the system’s energy usage and maneuverability, a control strategy with a variable pressure margin was designed. Meanwhile, in order to solve the problem that the hydraulic pump’s mechanical efficiency causes system pressure control deviation, a torque compensation method based on offline data and speed prediction was proposed. Finally, simulation and testing were used to confirm the viability of the control strategy. The test results show that: the system could realize stable pressure margin control, and the response rise time was within 0.7 s under a variety of flow circumstances; the system could follow the control instruction to change linearly and the flow rate changed smoothly in the adjustable pressure gap control; after using the compensation method, the deviation of the pressure gap control was within 2%.

The dead-zone input and hydraulic cylinder friction of the pump-controlled automatic gauge control (AGC) system introduce significant challenges to the high-precision rolling of lithium battery pole pieces. To address these nonlinearities, this paper establishes the friction and dead-zone model of the pump-controlled AGC system, and a slide-mode observer is designed to estimate the friction state z in the LuGre model. Furthermore, an adaptive compensation method is adopted to identify the unknown parameters of the input dead-zone and friction models. Meanwhile, combined with the framework of backstepping control design, both matched and mismatched disturbances are effectively compensated. Stability analysis guarantees the convergence of the estimation errors and closed-loop signal boundedness. Finally, experimental results validate the effectiveness and robustness of the proposed control strategy.

With the development of electrification and green technologies in construction machinery, servo pump-controlled technology has shown great potential in electric loaders due to its high efficiency and energy-saving characteristics. However, the complex coupling among multiple parameters makes it difficult to simultaneously optimize dynamic response and energy efficiency. To address this issue, a multi-objective parameter optimization method for servo pump-controlled units based on Sobol sensitivity analysis and the NSGA-II algorithm is proposed. First, an electro-hydraulic coupling model of the servo pump-controlled unit is established. Subsequently, Sobol global sensitivity analysis is employed to identify sensitive parameters affecting system performance, and a multi-objective optimization model is constructed with dynamic performance and energy efficiency as optimization objectives. Finally, the NSGA-II algorithm is adopted for coordinated parameter optimization, and the results are validated through MATLAB/Simulink simulations and experiments. Results show that the optimized system achieves improved dynamic response, stability, and energy efficiency, demonstrating the effectiveness of the proposed method for the parameter optimization of electric loader servo pump-controlled systems.