Conserve - Control and Optimisation of an Electric Food Transport System
To minimize the indirect emissions of food production and the pollutant emissions directly caused by temperature-controlled transport, today, intelligent solutions are needed to answer cities' food and drug supply problems. The efficient integration of energy-intensive additional auxiliaries into electrified LCV requires a holistic thermal management approach in system design, cargo space monitoring, condition description of the entire cooling system, and adequate adaptive control of the complex system.
The aim is to consider the entire process of temperature-controlled transport, including environmental conditions and route scenarios, in terms of integrated energy management - with the objective of maximizing the range of the vehicle with maximum availability of the cooling function.
We developed a holistic control concept to enable the most reliable temperature-controlled transport and increase efficiency and save energy while maximizing the driving range of refrigerated electric vehicles. This innovative control architecture combines model-predictive control for temperature-controlled cargo systems with the demanding constraints which come with the usage of an electric vehicle.
With methods of mixed-integer quadratic programming and system parameter identification, the holistic optimization of the energy management system can be achieved. Further methods of model reduction were developed to achieve a fast and robust state-of-health prediction and fault detection and isolation (FDI).
The proposed control concepts are validated via real measurements on a vehicle testbench (see image below). Next to an RDE (real driving cycle), which was adjusted with door openings, the environment temperature and solar radiation were modified to test the control performance in the worst-case scenarios. The overall controller performance was compared to a typical industrial proportional Integral (PI) controller.
On the other hand, the FDI solution was tested in a similar testbench that allowed to trigger different Fault scenarios and validate the developed FDI concept.
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Poks, Agnes, Markus Fallmann, Lorenz Fink, Lukas Rinnofner, and Martin Kozek. "Fault detection and isolation for a secondary loop refrigeration system, opens an external URL in a new window." Applied Thermal Engineering 227 (2023): 120277.
Fallmann, Markus, Agnes Poks, and Martin Kozek. "Model Predictive Control for Mobile Refrigeration Systems: Challenges and Approaches, opens an external URL in a new window." Science. Research. Pannonia (2022): 335-341.
Poks, Agnes, M. Fallmann and M. Kozek "Experimental validation of optimal recuperation strategy for electric cooling vehicle" (2022)
Poks, Agnes, Elisabeth Luchini, Filip Kitanoski, and Martin Kozek. "Wholistic simulation of an all-electric refrigerated delivery vehicle, opens an external URL in a new window." In 2020 SICE International Symposium on Control Systems (SICE ISCS), pp. 1-6. IEEE, 2020.
Luchini, Elisabeth, Agnes Poks, Dominik Radler, and Martin Kozek. "Model predictive temperature control for a food transporter with door-openings, opens an external URL in a new window." In 2020 SICE International Symposium on Control Systems (SICE ISCS), pp. 85-91. IEEE, 2020.
- February 2019 - October 2021