Hybrid power-trains for improved energy eficiency and safety in intermodal transport by railways



This technology describes innovative approach for which software model has been created in order to evaluate the energy efficiency of the battery-hybridized propulsion system equipped with an internal combustion engine and adapted for the utilization within a diesel-electric locomotive.

Technology Description

In order to make the existing rail transport more environmentally friendly, transport electrification is typically considered, which can be facilitated through rail route electrification or by means of power-train hybridization measures, typically through augmenting the existing diesel-electric propulsion system with the suitably-sized electrical energy storage system based on advanced lithium batteries.

One such approach to power-train battery hybridization has been developed in wherein an extensive software model has been created in order to evaluate the energy efficiency of the battery-hybridized propulsion system equipped with an internal combustion engine and adapted for the utilization within a diesel-electric locomotive of a freight train traveling over a mountainous rail route.

This comprehensive model comprises a rule-based control strategy for the hybridized power train, which schedules the diesel engine in such a way to achieve the minimum of fuel consumption, while also utilizing the battery energy storage system for additional power during freight train ascending to a higher altitude and regenerative braking in the case of freight train descending to lower altitudes.

Main advantages

The main perceived advantages of the proposed model of rail transportation over the traditional approaches to rail transportation planning are as follows:

  1. The proposed software model is capable of predicting the energy (fuel) consumption.
  2. The model can also estimate the cost-effectiveness of the particular traction system and can estimate the profitability and return-of-investment period.
  3. The model can be used to optimize the rail transport, and to improve the overall transportation safety by utilizing information from remote sensors networks.

Stage of development

The model has been extensively tested in lab (TRL-4) for the case of quite demanding freighting mission corresponding to a mountainous railway route and has so far, indicated the following results:

  1. Over 15% fuel efficiency improvement and proportional reduction of pollutant emissions.
  2. The estimated return-of-investment period of state-of-the-art lithium batteries is one quarter (25%) of battery system useful cycle life solely through fuel consumption reduction.
  3. Battery system operation can be further optimized and overall transportation safety can be increased.
  4. Hierarchical structure of the model, allows top-down of bottom-up rail transport optimization.

Challenge and needs

Transportation electrification has been recognized as a promising way to make the overall system more efficient, cleaner, quieter, and less dependent on oil reserves, while incorporating renewable energy sources into the overall energy system can further reduce air pollution and greenhouse gases emissions. The second crucial aspect of rail transport is its timely scheduling and operational safety, especially when increased autonomy of operation of railway vehicles is concerned. Utilization of fifth-generation (5G) new radio (NR) sensor networks in combination with advanced information fusion techniques offers distinct advantages over the GSM-R technology. These efforts are likely to herald a new era of Internet of Things (IoT) technologies applicable to railway transport, thus facilitating increased penetration of Industrial IoT into this sector and opening additional possibilities for intelligent railway transport.

Intellectual property

The technology is not yet protected by a patent.

Potential markets and targets

The developed software model could be of interest to national and regional railway fleet operators. Proposed solution may find its application within several global markets such as:

  • Smart Ports Market(global market is projected to reach USD 5.3 billion by 2024, at a CAGR of 25.0%),
  • Train Control Systems Market (global market is projected to reach USD 3.58 Billion by 2022, at a CAGR of 8.02%),

Hybrid Train Markets (market is projected to reach 9,109 units by 2030, at a CAGR of 4.8%).

Potential partners

Commercial partner, which possesses the expertise in installation, maintenance and operation of remote sensor networks, GPS systems and advanced next-generation sensor networks equipment. Partner would be tasked with the installation and operation of this equipment and collection of data, which will subsequently be provided to the research team for the purpose of model extension and validation.

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