Our research team utilises its knowledge of perishable products for design and evaluation of climate control systems. Insight in product quality development in relation to the product temperature and gas composition is exploited for product-oriented design and control of climate conditions.
Examples of R&D results
We analyse and optimise climate control systems for storage
facilities for perishable products: reefer containers, display cabinets,
isolated pallets and complete cold chains. Some examples:
- Product-oriented control of storage conditions for use in the processing industry. For example, a Model-Predictive Controller (MPC) has been developed that controls potato quality development through the climate conditions, aiming at an optimal quality at the end of storage.
- Controlled quality development or ripening of fruits and vegetables in a reefer container with a reduced energy consumption. By combining knowledge of the agro product with insight in the thermodynamic behaviour and product-gas interaction, an advanced climate control algorithm is being developed. This system combines a controlled product quality development with reduced climate control energy consumption.
- Information and measurement system for prediction of quality development of perishable products during transport. A model is used to predict the storage climate from logistic data. The system output is an estimate of the product quality at the end of the trip.
Research on interaction of product and
storage facilities
Our research in climate control links product knowledge with
thermodynamic behaviour in storage facilities to describe and predict the
product quality development:
- Product knowledge
- Thermodynamic research
The quality development of
agro-products is largely dependent on the temperature,
humidity and gas composition.
Product research at EC-Pack results in an
increasing number of quality development models for fruits and vegetables.
Model studies and practical experiments are set up to describe the interaction of the cool unit, the stowage space and the perishable product. These relate the transport climate to external factors like cooling, ventilation, insulation and cool unit control systems. The main focus is on thermodynamic behaviour, including heat and moisture generation by the product (respiration). When needed, the gas composition is also included, e.g. to verify the effect of CA control.
Depending on the complexity of the problem and the desired accuracy, different modelling techniques may be chosen, such as Computational Fluid Dynamics, or Network Dynamics.
Objectives
- extended product storage life
- improved preservation of product quality
- reduced energy consumption of the climate control unit, while maintaining the product quality
Experimental research on thermodynamic behaviour of a filled reefer container
For storage improvement of perishables, various types of process control algorithms, varying from PID controllers to Model-Predictive Control (MPC), have been developed.
MPC is a model-based control strategy that considers product-essential product properties development in relation to on-line measurements and control actions.
A dynamic process/product model is used to predict the process output within a time horizon for the computation of future input adjustments.
Since MPC is based on explicit product knowledge, it is very suitable for product-oriented climate control.
