Telemetry Data Compression for Battery Electric Vehicle Energy Consumption

M.H.M. Baart; Igo J.M. Besselink; Henk Nijmeijer

Telemetry Data Compression for Battery Electric Vehicle Energy Consumption

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic

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Abstract

Telemetry data is used to model and assess the energy consumption of battery electric buses. This paper presents telemetry data compression methods, which require less communication bandwidth to capture the energy consumption data without a loss of accuracy. These methods include calculating the longitudinal acceleration more reliably and reordering the energy consumption calculation process to include all acceleration events, even at low sample rates. Two of the developed methods can reduce the data transfer by 39%, while the energy consumption error does not increase.

Original language	English
Title of host publication	Towards Intelligent E-Mobility—Selected Papers from The 34th International Electric Vehicles Symposium and Exhibition
Number of pages	11
Publication status	Published - 25 Jun 2021
Event	34th International Electric Vehicle Symposium and Exhibition (EVS34) - Nanjing, China Duration: 25 Jun 2021 → 28 Jun 2021 http://www.evs34.org.cn/

Conference

Conference	34th International Electric Vehicle Symposium and Exhibition (EVS34)
Abbreviated title	EVS34
Country/Territory	China
City	Nanjing
Period	25/06/21 → 28/06/21
Internet address	http://www.evs34.org.cn/

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

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2021_EVS34paper_TelemetryDataCompressionFinal published version, 2.32 MB

Cite this

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title = "Telemetry Data Compression for Battery Electric Vehicle Energy Consumption",

abstract = "Telemetry data is used to model and assess the energy consumption of battery electric buses. This paper presents telemetry data compression methods, which require less communication bandwidth to capture the energy consumption data without a loss of accuracy. These methods include calculating the longitudinal acceleration more reliably and reordering the energy consumption calculation process to include all acceleration events, even at low sample rates. Two of the developed methods can reduce the data transfer by 39\%, while the energy consumption error does not increase.",

keywords = "BEV, data acquisition, energy consumption, public transport",

author = "M.H.M. Baart and Besselink, \{Igo J.M.\} and Henk Nijmeijer",

year = "2021",

month = jun,

day = "25",

language = "English",

booktitle = "Towards Intelligent E-Mobility—Selected Papers from The 34th International Electric Vehicles Symposium and Exhibition",

note = "34th International Electric Vehicle Symposium and Exhibition (EVS34), EVS34 ; Conference date: 25-06-2021 Through 28-06-2021",

url = "http://www.evs34.org.cn/",

}

TY - GEN

T1 - Telemetry Data Compression for Battery Electric Vehicle Energy Consumption

AU - Baart, M.H.M.

AU - Besselink, Igo J.M.

AU - Nijmeijer, Henk

PY - 2021/6/25

Y1 - 2021/6/25

N2 - Telemetry data is used to model and assess the energy consumption of battery electric buses. This paper presents telemetry data compression methods, which require less communication bandwidth to capture the energy consumption data without a loss of accuracy. These methods include calculating the longitudinal acceleration more reliably and reordering the energy consumption calculation process to include all acceleration events, even at low sample rates. Two of the developed methods can reduce the data transfer by 39%, while the energy consumption error does not increase.

AB - Telemetry data is used to model and assess the energy consumption of battery electric buses. This paper presents telemetry data compression methods, which require less communication bandwidth to capture the energy consumption data without a loss of accuracy. These methods include calculating the longitudinal acceleration more reliably and reordering the energy consumption calculation process to include all acceleration events, even at low sample rates. Two of the developed methods can reduce the data transfer by 39%, while the energy consumption error does not increase.

KW - BEV

KW - data acquisition

KW - energy consumption

KW - public transport

M3 - Conference contribution

BT - Towards Intelligent E-Mobility—Selected Papers from The 34th International Electric Vehicles Symposium and Exhibition

T2 - 34th International Electric Vehicle Symposium and Exhibition (EVS34)

Y2 - 25 June 2021 through 28 June 2021

ER -

Telemetry Data Compression for Battery Electric Vehicle Energy Consumption

Abstract

Conference

UN SDGs

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