Intelligent Regulation Algorithms for Electron Beam High-Voltage Power Supplies

Electron beam technology, as a core support for high-end manufacturing and precision processing, relies directly on the accuracy and stability of high-voltage power supply systems. These power supplies must not only provide stable acceleration voltage (typically 30-60 kV) but also achieve coordinated control of multiple parameters such as beam current and focus current, with precision requirements within 0.1%, to ensure uniform distribution of electron beam energy density. Traditional control strategies such as Pulse Width Modulation (PWM) and Pulse Frequency Modulation (PFM) are widely used but suffer from limitations including significant switching losses and poor stability under light loads. With the development of Digital Signal Processors (DSP) and intelligent algorithms, the regulation methods for electron beam high-voltage power supplies are undergoing revolutionary changes.
The core of intelligent regulation algorithms lies in achieving precise output of high-voltage power supplies through real-time monitoring and dynamic response. The Proportional-Integral-Derivative (PID) algorithm is the most widely applied basic solution, adjusting output in real-time by processing feedback signals of voltage and current. In electron beam welding and melting processes, the PID algorithm can effectively suppress voltage fluctuations and ensure beam stability. For example, the integral-separation PID algorithm cancels the integral function when large deviations occur in the system to avoid overshoot; when deviations are small, it introduces integral control to eliminate steady-state errors, thereby improving response speed and control accuracy. However, the PID algorithm depends on accurate mathematical models and performs poorly under nonlinear loads or complex working conditions.
To address complex working conditions, fuzzy logic algorithms break away from the constraints of traditional mathematical models. This algorithm constructs inference rules based on fuzzy language descriptions such as low voltage or severe current fluctuation, mimicking human empirical decision-making. In electron beam additive manufacturing, when changes in material thermal conductivity cause load fluctuations, fuzzy logic can intelligently adjust output parameters to maintain stable power supply. Experiments show that this algorithm can improve the surface roughness of titanium alloy formations by 40%.
Multi-objective optimization algorithms represent a cutting-edge development direction, particularly suitable for scenarios such as system-on-chip testing that require balancing voltage accuracy, current stability, and energy efficiency. By employing evolutionary algorithms or particle swarm optimization, these algorithms weigh multiple objective functions to explore optimal output strategies. For example, in electron beam selective melting processes, multi-objective optimization can meet millivolt-level voltage accuracy while reducing overall energy consumption by 10-15%.
Digital twin technology and adaptive control algorithms further expand the boundaries of intelligent regulation. Digital twins construct multi-physical field models of power supply-electron gun-molten pool, enabling virtual debugging of parameter combinations and reducing the number of physical tests by more than 50%. Deep reinforcement learning algorithms can dynamically adjust voltage-current curves to adapt to the dynamic thermal conduction characteristics of different materials, increasing energy utilization by 25%.
The implementation of intelligent algorithms relies on high-performance hardware platforms. DSPs, with their powerful computing capabilities and real-time sampling functions, have become the core for algorithm deployment. Field-Programmable Gate Arrays (FPGA) are used to accelerate complex computations, ensuring nanosecond-level response. In the future, with the promotion of SiC power devices and modular design, intelligent regulation algorithms will further evolve toward higher efficiency, integration, and adaptability, providing solid support for the application of electron beam technology in high-precision fields.