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Predictive Energy Management for Recuperation Axles in Refrigerated Trailers

Dennis Bank, Simon F. G. Ehlers, Karl-Philipp Kortmann, Tobias Zeller, Patrick Cujic, Thomas Seel

Abstract

Refrigerated truck trailers are currently mainly operated with environmentally harmful diesel units; an alternative is to operate the refrigeration unit with electrical energy. However, this requires a battery, the size of which can be reduced by using a recuperation axle, which recovers energy during braking. Current systems work purely reactively and often in so-called towing mode, in which a generator torque is provided without a braking request from the driver in order to secure the energy supply. However, this drag leads to additional consumption in the truck. This work quantifies the potential of predictive energy management that uses route and environmental data to minimize CO2 emissions. This was done using simulation data obtained with the help of VECTO. It was shown that there is still considerable potential for savings, so this paper provides an important basis for the later development of predictive energy management and, thus, for the electrification of refrigerated truck transports.

Predictive Energy Management for Recuperation Axles in Refrigerated Trailers

Abstract

Refrigerated truck trailers are currently mainly operated with environmentally harmful diesel units; an alternative is to operate the refrigeration unit with electrical energy. However, this requires a battery, the size of which can be reduced by using a recuperation axle, which recovers energy during braking. Current systems work purely reactively and often in so-called towing mode, in which a generator torque is provided without a braking request from the driver in order to secure the energy supply. However, this drag leads to additional consumption in the truck. This work quantifies the potential of predictive energy management that uses route and environmental data to minimize CO2 emissions. This was done using simulation data obtained with the help of VECTO. It was shown that there is still considerable potential for savings, so this paper provides an important basis for the later development of predictive energy management and, thus, for the electrification of refrigerated truck transports.
Paper Structure (9 sections, 9 figures, 2 tables)

This paper contains 9 sections, 9 figures, 2 tables.

Table of Contents

  1. Introduction
  2. Trailer & Drivecycle Modelling
  3. VECTO
  4. Drive Cycles
  5. Electrified Trailer
  6. Towing Optimization
  7. Results
  8. Conclusion and future work
  9. Acknowledgment

Figures (9)

  • Figure 1: Overview of an electrified, refrigerated trailer. A generator is added in one of the axles to reduce the battery size and ensure the supply of energy to the TRU during the whole drive
  • Figure 2: Schematic representation of a predictive EMS. It could use different information about the route, current traffic, etc., to optimize the selection of the current operating mode and thus reduce the emissions of the system
  • Figure 3: The three modified drive cycles represent urban, regional, and long-haul traffic deliveries. As can be seen, the average speed and the driving dynamics vary widely between the different drive cycles, giving good coverage of possible driving scenarios.
  • Figure 4: The optimal lower and upper bounds for the urban delivery cycle are 45% and 50%, resulting in an additional fuel consumption of 8.9l in the truck
  • Figure 5: For the regional delivery cycle, the optimal lower and upper bound values are 25% and 50%, resulting in additional fuel consumption of 2.2l of diesel
  • ...and 4 more figures