HVAC operation planning for electric bus trips based on chance-constrained programming

Turning on the heating, ventilation and air-conditioning (HVAC) system is one effective measure to improve the thermal comfort of passengers in an electric bus (EB). However, it will also increase the consumption of the battery power. For an EB with limited battery capacity and that can only be char...

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Bibliographic Details
Published in:Energy (Oxford) Vol. 258; p. 124807
Main Authors: Bie, Yiming, Liu, Yajun, Li, Shiwu, Wang, Linhong
Format: Journal Article
Language:English
Published: Elsevier Ltd 01.11.2022
Subjects:
batteries
case studies
Chance constrained programming
Electric bus
energy
HAVC system
heat
Operation planning
system optimization
temperature
Thermal comfort
Electric bus
Operation planning
Thermal comfort
Chance constrained programming
HAVC system
ISSN:0360-5442
Online Access:Get full text
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Summary:Turning on the heating, ventilation and air-conditioning (HVAC) system is one effective measure to improve the thermal comfort of passengers in an electric bus (EB). However, it will also increase the consumption of the battery power. For an EB with limited battery capacity and that can only be charged at night, it is impossible to keep the HVAC on for all-day trips. This study aims to develop a daily HVAC operation planning model for an EB to maximize the thermal comfort of the passengers under the constraint of battery capacity. Firstly, we developed a cabin temperature estimation model to quantify the thermal comfort of the passengers. Secondly, considering the stochastic volatility of trip energy consumption, the chance-constrained programming based HVAC planning model is established, to determine the optimal HVAC gear of each trip. Finally, a real EB is taken as an example and field operational data collected in three different seasons are used in the case study. Results show that passenger's thermal comfort can be improved in different seasons after applying the proposed optimization method while avoiding the service interruption due to running down of battery power. •A daily HVAC system usage optimization model for an EB is proposed.•Estimation models for cabin temperature and trip energy consumption are developed.•Passenger thermal comfort is maximized considering limited battery capacity.•Real EB operational data in three seasons are used to validate the proposed models.
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ISSN:0360-5442
DOI:10.1016/j.energy.2022.124807