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HETEROGENEOUS BATTERY SYSTEMS IN BATTERY EQUIPPED PASSENGER TRAINS
Mälardalen University, School of Innovation, Design and Engineering.
Mälardalen University, School of Innovation, Design and Engineering.
2021 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

The rise of batteries in the industry, especially Li-ion, is increasing rapidly. Li-ion battery systems are traditionally composed of a particular type of cell chemistry fit to the system needs. Due to the significant differences between chemistries, different cells have different attributes. The thesis explores the potential of a heterogeneous solution to include different cells to find a suitable compromise between different attributes. An electrified passenger train using a homogenous solution was evaluated against a heterogeneous solution consisting of two cell types, NMC and LTO, which have significant differences in attributes.  Simulation with models covering the train kinematics, track characteristics, and battery behaviour generates the thesis results. Validation of simulation results includes comparing previous simulations and the new effects of the heterogeneous solution, which indicate a good fit. Verification of the results encompasses a small-scale experiment with a custom-made physical circuit to observe the proposed solution's actual behaviour and verify model validity, which implies the correctness of models and implementation. The results indicate that a heterogeneous solution is possible within the scope of electrified trains. Furthermore, several trade-offs exist between NMC and LTO cells, especially regarding rate capability, safety and capacity, which confirms the potential of heterogeneous battery systems. 

Place, publisher, year, edition, pages
2021. , p. 156
Keywords [en]
LabVIEW, MATLAB, Simulink, Control theory, Battery, Batteries, Li-ion, Heterogeneous batteries, LTO, NMC, Electronics, Electrical, Engineering, Simulation, Trains, SysML, UML, LTSpice, Design of experiments, DOE, Sensor technology, Railway, EV, Electrical vehicles
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:mdh:diva-54482OAI: oai:DiVA.org:mdh-54482DiVA, id: diva2:1560634
External cooperation
Alstom
Subject / course
Aeronautical Engineering; Computer Science
Supervisors
Examiners
Available from: 2021-06-21 Created: 2021-06-04 Last updated: 2025-10-10Bibliographically approved

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Citation style
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