Sorption heat pumps are employed in various heat-driven cooling and heat pumping applications. These heat pumps may be driven by solar energy, natural gas, biogas, geothermal energy or waste heat. Given that a plethora of heat sources and sorption materials can be exploited for different applications, various sorption heat pump modules have been developed. The sorption modules are pre-engineered sorption components for increased ease of sorption system development, improved cost effectiveness and reduced system complexity for various applications. However, in the design of sorption modules, component and system modelling and simulation are useful in the process of determining the optimal candidate of several possible sorption working couples for a given application. A test platform has been developed and a test methodology devised for the rapid characterisation of the transient behaviour of the sorption modules. The testing apparatus was used to derive various model parameters to be used for validation of a dynamic sorption module component model. The test method was analogous to that employed for dynamic testing and performance modelling of electrochemical accumulators (i.e. electric batteries) given the similarities between them and sorption modules (also known as thermochemical accumulators). The model parameter identification was based on various heating and cooling power performance parameters as a function of state of charge (SoC) of the sorption modules. A 7-step procedure was used to characterise the performance of the sorption modules based on experimental data. A reference performance for charge and discharge of the sorption modules was measured followed by several measurements at ‘off-reference’ conditions. Performance curves for ‘off-reference’ conditions were then correlated to reference conditions to generate performance curves that describe the transient cooling and heating power delivery of the sorption module at any point within the test range. Results showed that the discharge performance of the sorption modules could be predicted within a reasonable margin of error with a test run sequence of 39 cycles.