## 1 Introduction  
The concept of future factories demands new designs and developments of sustainable, energy-efficient, and intelligent hydraulic systems and components. Industry 4.0, along with key enablers such as the Industrial Internet of Things (IIoT), standardized communication protocols (e.g., OPC-UA), new data transfer methods, and AI-based approaches, as well as facilitated efficient data gathering, transfer, and analytics [1]. Conversely, factories of the future rely on various approaches such as modular design with plug-and-play capabilities, distributed systems with integrated local intelligence, 5G and edge computing, cyber-physical systems (CPSs), and data-driven digital twins, among others [2]. In these intelligent systems and components, self-awareness, health monitoring, and predictive maintenance are incorporated. To successfully digitize a system or component and effectively monitor or evaluate its behaviour, key characteristics must be defined, stored in local clouds, and made available for further use and services. This paper focuses on the design of a new actuator system integrated into a hydraulic on/off valve, which is used in hydraulic digital fluid control units (DFCUs), and its representation of static and dynamic performance. Digital hydraulics and DFCUs constructed from on/off valves offer several advantages over conventional hydraulics and sliding spool valves, including a higher power density, precise control, greater force output, and improved energy efficiency [3]. Furthermore, digital hydraulics combined with a piezoelectric actuator system has the potential to significantly improve electrical energy efficiency, as well as enhance the static and dynamic performance of hydraulic valves, such as DFCUs [4]. The most commonly used actuators in conventional hydraulics are electromagnetic actuators (solenoids), which are robust and reasonably priced. However, their performance is limited when switchovertimes below 1 ms are required, a key factor for DFCUs in high-dynamic and high-precision hydraulic linear drives. As noted by the authors in [3], some commercially available on/off valves used in digital fluid power systems have response times ranging from 3 to 10 ms. Shorter switchover and response times are hindered by magnetic induction and eddy currents when switching the electrical current on. Differences in the static and especially the dynamic characteristics of any type of hydraulic valve, when combined with a control method, have a significant impact on hydraulic linear drive behaviour, including stroke resolution, precise uniform motion, step response, and operational stability [5].  
By using alternative actuators, particularly piezoelectric actuators, which offer the best practical potential, significantly shorter response times and a lower electrical energy consumption can be achieved, especially in the steady active state [6; 7; 8; 9]. On the one hand, the switchover times of electromagnetic actuators range between 10 and 20 ms, while on the other hand, piezoelectric actuators can achieve switchover times of less than 1 ms. In addition to these advantages, piezoelectric actuators offer high precision, flexible stroke control, immunity to electromagnetic interference, and structural scalability [10].  
This paper begins by presenting the theoretical background of piezoelectric actuators and piezoelectricity, explaining both the direct and inverse piezoelectric effects, along with the core concept of the actuator-sensor approach. The following section focuses on the design and functionality of the piezoelectric actuator system, followed by a detailed explanation of the experimental methodology. The main part of the paper presents the experimental characterization of the static and dynamic performance of the piezoelectric actuator system, which serves as the foundation for developing a smart actuator system concept. The proposed actuator administration shell concept will be used in the future development of a real actuator-sensor system, as well as switching valves and DFCUs.