Battery health target tracking for HEVs: Closed-loop control approach, simulation framework, and reference trajectory optimization

Widmer, Fabio; Ritter, Andreas; Ritzmann, Johannes; Garcı́a-Dorado, David; Onder, Christopher H.

doi:10.1016/j.etran.2023.100244

Cited by 2 publications

(1 citation statement)

References 28 publications

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“…(4) The optimal design and control of a thermal energy buffer in an electric city bus was studied based on the passenger loads, velocity and elevation profiles 15 . (5) A set of 16 representative all-day driving missions served to optimize the bus operation in terms of managing battery degradation throughout the vehicle lifetime 16 . (6) Hourly-averaged data was used to conduct a large-scale sensitivity analysis of the thermal comfort systems, allowing a comparison of various heating, ventilation and air conditioning (HVAC) systems 17 .…”

Section: Background and Summarymentioning

confidence: 99%

ZTBus: A Large Dataset of Time-Resolved City Bus Driving Missions

Widmer,

Ritter,

Onder

2023

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This paper presents the Zurich Transit Bus (ZTBus) dataset, which consists of data recorded during driving missions of electric city buses in Zurich, Switzerland. The data was collected over several years on two trolley buses as part of multiple research projects. It involves more than a thousand missions across all seasons, each mission usually covering a full day of operation. The ZTBus dataset contains detailed information on the vehicle’s power demand, propulsion system, odometry, global position, ambient temperature, door openings, number of passengers, dispatch patterns within the public transportation network, etc. All signals are synchronized in time and include an absolute timestamp in tabular form. The dataset can be used as a foundation for a variety of studies and analyses. For example, the data can serve as a basis for simulations to estimate the performance of different public transit vehicle types, or to evaluate and optimize control strategies of hybrid electric vehicles. Furthermore, numerous influencing factors on vehicle operation, such as traffic, passenger volume, etc., can be analyzed in detail.

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Section: Background and Summarymentioning

confidence: 99%