Energy Uncertainty Analysis of Electric Buses

Jari Vepsäläinen,Antti Lajunen,Klaus Kivekäs,Kari Tammi,Antti Ritari

doi:10.3390/en11123267

Jari Vepsäläinen, Antti Lajunen + Show 3 more

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https://doi.org/10.3390/en11123267

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Journal: Energies	Publication Date: Nov 23, 2018
Citations: 39	License type: CC BY 4.0

Affiliation: Aalto University, University of Helsinki

Abstract

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.

Highlights

Battery electric buses (BEBs) have recently emerged as an environmentally friendly, yet expensive alternative for diesel buses [1]
The analysis focused on determining which factors were the main contributors to the variation in the energy consumption rate (ECR), energy regeneration, and internal resistance of the battery
We found that up to 18% of the ECR variation of BEBs is caused by rolling resistance variation and 13% by payload variation

Summary

Introduction

Battery electric buses (BEBs) have recently emerged as an environmentally friendly, yet expensive alternative for diesel buses [1]. Variation in ECR may cause delays in the charging schedules, which are hard to predict, because such delays have not been an issue with diesel buses. The sensitivity of ECR and charging efficiency require detailed investigation with real-world data to ease the transition to fully electric public transportation. Most engineering systems have input values—some adjustable, and some noisy and unpredictable. Most engineering have input because values—some adjustable, and some noisy. The adjustable factors cansystems have minor variation of tolerances, but the unpredictable factorsand can unpredictable. The factors input factor propagates into variation the systembut output unpredictable factors can have quantification much more variation. Uncertainty (UQ) is a The method to factor show the variation in the system variation in the system output and performance

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