scholarly journals Developing a model for analysis of the cooling loads of a hybrid electric vehicle by using co-simulations of verified submodels

2017 ◽  
Vol 232 (6) ◽  
pp. 766-784 ◽  
Author(s):  
Sina Shojaei ◽  
Andrew McGordon ◽  
Simon Robinson ◽  
James Marco ◽  
Paul Jennings
Keyword(s):  
Electric Vehicle ◽  
Air Conditioning ◽  
Hybrid Electric Vehicle ◽  
System Level ◽  
Integrated Modelling ◽  
Ambient Conditions ◽  
Simulation Speed ◽  
Duty Cycles ◽  
Hybrid Electric ◽  
Cooling Loads

The requirement for including the air-conditioning and the battery-cooling loads within the energy efficiency analyses of a hybrid electric vehicle is widely recognized and has promoted system-level simulations and integrated modelling, escalating the challenge of balancing the accuracy and the speed of simulations. In this paper, a hybrid electric vehicle model is created through co-simulation of the passenger cabin, the air conditioning, the battery cooling, and the powertrai. Calibration and verification of the submodels help determine their accuracy in representing the target vehicle and achieve a balance between the model fidelity and the simulation speed. The result is a model which has a higher accuracy and a higher speed than those of similar models developed previously and which provides a reliable tool for a thorough investigation of the cooling loads for different ambient conditions and different duty cycles.

Modeling of Thermal Dynamics of a Connected Hybrid Electric Vehicle for Integrated HVAC and Powertrain Optimal Operation

2019 ◽  
Author(s):  
Nehal Doshi ◽  
Drew Hanover ◽  
Sadra Hemmati ◽  
Christopher Morgan ◽  
Mahdi Shahbakhti
Keyword(s):  
Electric Vehicle ◽  
Hybrid Electric Vehicle ◽  
Optimal Operation ◽  
Operating Conditions ◽  
System Level ◽  
Electric Heater ◽  
Ambient Conditions ◽  
Ic Engine ◽  
Thermal Dynamics ◽  
Hybrid Electric

Abstract Integrated energy management across system level components in electric vehicles (EVs) is currently an under-explored space. Opportunity exists to mitigate energy consumption and extend usable range of EVs through optimal control strategies which exploit system dynamics via controls integration of vehicle subsystems. Additionally, information available in connected vehicles like driver schedules, trip duration and ambient conditions can be leveraged to predict the operating conditions for a vehicle when a validated model of the vehicle is known. In this study, data-driven and physics-based models for heating, ventilation and air-conditioning (HVAC) are developed and utilized along with the vehicle dynamics and powertrain (VD&PT) models for a hybrid electric vehicle (HEV). The integrated HVAC and VD&PT models are then validated against real world data. Next, an integrated relationship between the internal combustion (IC) engine coolant and the cabin electric heater is established and used to promote potential energy savings in cabin heating when the operating schedule is known. Finally, an optimization study is conducted to establish a control strategy which maximizes the HVAC energy efficiency whilst maintaining occupant comfort levels according to ASHRAE standards and improving usable range of the vehicle relative to its baseline calibration.

Comparison of economic viability of series and parallel PHEVs for medium-duty truck and transit bus applications

2020 ◽  
Vol 234 (10-11) ◽  
pp. 2458-2472
Author(s):  
Vaidehi Hoshing ◽  
Ashish Vora ◽  
Tridib Saha ◽  
Xing Jin ◽  
Gregory Shaver ◽  
...  
Keyword(s):  
Electric Vehicle ◽  
Hybrid Electric Vehicle ◽  
Cost Savings ◽  
Parallel Architectures ◽  
Economic Viability ◽  
Fuel Price ◽  
Vehicle Class ◽  
Duty Cycles ◽  
Hybrid Electric ◽  
Transit Bus

This article performs a novel comparison of the life-cycle costs of the series and parallel architectures for plug-in hybrid electric vehicles. Economic viability is defined as having a payback period less than 2 years and number of battery replacements less than or equal to three over a vehicle life of 12 years along-with drivability and gradability constraints. Economic viability is compared for two plug-in hybrid electric vehicle applications (Medium-duty Truck and Transit Bus) using series and parallel architectures over multiple drivecycles, for three economic scenarios (viz. 2020, 2025 and 2030 where the fuel price, battery price and motor price are varied such that latter scenarios are more favorable for hybridization). One battery overnight recharge is assumed. The results demonstrate that by 2020 the plug-in hybrid electric vehicle transit buses are viable for the duty cycles Manhattan, Orange County, and China (Normal and Aggressive). By 2025, plug-in hybrid electric vehicle Class 6 trucks are viable for all duty cycles considered (Pick-up and delivery, Refuse and New York Composite). The parallel architectures generally require less than 50% of the initial cost of the series architecture, due to smaller motor sizes, driving earlier viability for parallel architectures. The transit bus scenarios generally achieve payback sooner than the medium-duty truck due to higher fuel cost savings, driving earlier viability for transit bus applications.

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