High-precision temperature control systems based on thermoelectric cooling (TEC) have critical applications in maintaining the stability and operational precision of advanced semiconductor optoelectronic devices, including single-frequency semiconductor lasers, optical frequency combs, and photometric measurement systems. However, the intrinsic high thermal inertia and nonlinear electro-thermal coupling characteristics of TEC systems make it challenging for traditional Proportional-Integral-Derivative (PID) control algorithms to achieve the required millikelvin-level (mK) precision due to their tendency toward overshoot and oscillation.
In response to these issues, this paper thoroughly investigates the internal electro-thermal conversion mechanisms, heat conduction, and dissipation dynamics of TEC systems, proposing a high-precision temperature control approach based on an equivalent circuit model. By accurately constructing and verifying this equivalent circuit model, the study analyzes the oscillation characteristics and limitations inherent in traditional PID control, subsequently introducing an adaptive PID algorithm incorporating dynamic DC bias for enhanced precision.
Specifically, the algorithm utilizes a conventional PID strategy to rapidly approximate the target temperature during initial control stages. As the system nears the target temperature and temperature fluctuations decrease, it automatically transitions to an adaptive high-precision PID mode with dynamic DC bias. In this adaptive mode, the system continuously calculates the average output current and integrates temperature control errors over recent intervals, dynamically adjusting the overall control output via adaptive weighting and bias calculation to effectively counteract both gradual and transient environmental disturbances. Additionally, the algorithm employs an enhanced control strategy incorporating dual-temperature sensing, primarily leveraging dynamic analysis of the hot-side temperature measurement to anticipate and counteract thermal disturbances. This predictive feedforward compensation, based on analyzing the rapid dynamic trends of the hot-side temperature, enables the controller to react preemptively to fast-changing disturbances before they significantly affect the controlled object, thereby substantially improving overall system stability and precision.
Simulation results demonstrate that the proposed adaptive PID algorithm with dynamic DC bias can consistently maintain temperature control accuracy at the millikelvin level. It effectively mitigates transient and gradual environmental temperature disturbances, exhibiting excellent robustness against varying PID parameter settings. Furthermore, the core logic of the algorithm remains straightforward, computationally efficient, and hardware-friendly, making it particularly suited for embedded system implementations and practical engineering deployments.
In conclusion, the high-precision adaptive PID temperature control strategy presented herein offers significant theoretical and practical value by addressing inherent TEC system challenges through detailed internal modeling and adaptive control strategies, contributing both theoretically and practically to high-precision temperature control engineering.