Battery Design for Successful Electrification in Public Transport

Rothgang, Susanne; Rogge, Matthias; Becker, Jan; Sauer, Dirk Uwe

doi:10.3390/en8076715

Cited by 39 publications

(23 citation statements)

References 38 publications

(50 reference statements)

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“…However, this would significantly increase the efforts in planning and handling of the buses and is therefore not desired by bus operators. A more detailed discussion of the battery design for public transport applications is provided in [43].…”

Section: Operational Characteristicsmentioning

confidence: 99%

Electric bus fleet size and mix problem with optimization of charging infrastructure

Rogge

Hurk²,

Larsen³

et al. 2018

Applied Energy

Self Cite

239

111

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Section: Operational Characteristicsmentioning

confidence: 99%

Electric bus fleet size and mix problem with optimization of charging infrastructure

Rogge

Hurk²,

Larsen³

et al. 2018

Applied Energy

Self Cite

239

111

View full text Add to dashboard Cite

show abstract

“…A small battery is less flexible and prone to faster aging because of the fast charging, which is often done just barely within the limits of its capabilities. Rothgang et al [19] highlighted that the battery capacity and charging power should be set carefully for each bus network in mind. Moreover, Sinhuber et al [20] proposed that the BEB energy storage could be modular to adapt the bus for changing mission profiles.…”

Section: State-of-the-artmentioning

confidence: 99%

Energy Uncertainty Analysis of Electric Buses

et al. 2018

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Uncertainty in operation factors, such as the weather and driving behavior, makes it difficult to accurately predict the energy consumption of electric buses. As the consumption varies, the dimensioning of the battery capacity and charging systems is challenging and requires a dedicated decision-making process. To investigate the impact of uncertainty, six electric buses were measured in three routes with an Internet of Things (IoT) system from February 2016 to December 2017 in southern Finland in real operation conditions. The measurement results were thoroughly analyzed and the operation factors that caused variation in the energy consumption and internal resistance of the battery were studied in detail. The average energy consumption was 0.78 kWh/km and the consumption varied by more than 1 kWh/km between trips. Furthermore, consumption was 15% lower on a suburban route than on city routes. The energy consumption was mostly influenced by the ambient temperature, driving behavior, and route characteristics. The internal resistance varied mainly as a result of changes in the battery temperature and charging current. The energy consumption was predicted with above 75% accuracy with a linear model. The operation factors were correlated and a novel second-order normalization method was introduced to improve the interpretation of the results. The presented models and analyses can be integrated to powertrain and charging system design, as well as schedule planning.

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“…End terminus charging refers to recharging at the start or end terminus on every driving cycle. High-power lithium titanate batteries (LTO) are best suited to end terminus charging because they are eligible for high current charging [4], [5]. However, even if the bus size and battery chemistry are predetermined, the operation schedule and charging power vary case by case.…”

Section: A Motivationmentioning

confidence: 99%

Cost-Benefit Analysis of Electric Bus Fleet with Various Operation Intervals

Vepsäläinen

Baldi

Lajunen

et al. 2018

2018 21st International Conference on Intelligent Transportation Systems (ITSC)

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Electric buses are particularly suitable for city and suburban routes due to zero local exhaust and noise emissions. The operation schedule interval defines the charging power, bus fleet size and total cost of ownership of a bus. We propose a novel cost-benefit method for the scheduling of an electric city bus fleet on a single route. Three different charging infrastructure scenarios were considered. In the first scenario, only one charging station was used. The second scenario considered two charging stations that were located at the same terminus. In the third scenario, two charging stations were located at opposite terminuses. The costs and utilization rates of the buses were analyzed with operation intervals up to 40 minutes. The first scenario with a single charging station had the lowest costs for the entire bus fleet system when the utilization rate was considered. Furthermore, the results show that certain schedule intervals are more cost-beneficial in terms of vehicle specific life-cycle costs than others. In the future, the proposed method is expanded to aid the design of bus network scheduling under energy demand uncertainty.

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Battery Design for Successful Electrification in Public Transport

Cited by 39 publications

References 38 publications

Electric bus fleet size and mix problem with optimization of charging infrastructure

Electric bus fleet size and mix problem with optimization of charging infrastructure

Energy Uncertainty Analysis of Electric Buses

Cost-Benefit Analysis of Electric Bus Fleet with Various Operation Intervals

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