There are always differences between the computer predicted temperatures of a spacecraft thermal model and the temperatures measured during the mandatory laboratory thermal tests. As a consequence, the model must be correlated before the spacecraft is launched to space, in order to identify the correct parameters that match the experimentally measured temperatures.

A new technique is presented to identify the parameters, based on the minimization of the error of the transient equations which governs the heat transfer in the spacecraft. The steady state minimization was presented in a previous work, but the transient techniques presented hereafter enable a better and more extended identification of parameters despite the higher complexity of the computational problem.

The use of a set of available subroutines (TOLMIN), which permits the constrained optimization of a general function, makes possible to ensure that the obtained parameters are non-negative, a requirement to have physical sense. The gradient function must be calculated for each problem, but this can be done automatically.

Results show that for small and medium size transient Thermal Mathematical Models (TMM), a good correlation of thermal parameters can be achieved even if some of the nodes temperatures are not measured in the thermal tests.

航天器热模型的计算机预测温度与强制性实验室热测试期间测量的温度之间总是存在差异。因此，必须在航天器发射到太空之前关联模型，以便确定与实验测量温度相匹配的正确参数。

提出了一种新技术来识别参数，该技术基于控制航天器传热的瞬态方程的误差最小化。稳态最小化在先前的工作中提出，但是尽管计算问题的复杂性更高，但此后提出的瞬态技术能够更好和更扩展地识别参数。

使用允许对一般函数进行约束优化的一组可用子程序 (TOLMIN) 可以确保获得的参数是非负的，这是具有物理意义的要求。必须为每个问题计算梯度函数，但这可以自动完成。

结果表明，对于中小型瞬态热数学模型（TMM），即使在热测试中没有测量某些节点温度，也可以实现热参数的良好相关性。