Research

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24 pages, 6100 KiB

Open AccessArticle

Multi-Objective Optimisation-Based Design of an Electric Vehicle Cabin Heating Control System for Improved Thermal Comfort and Driving Range

by Ivan Cvok, Igor Ratković and Joško Deur

Energies 2021, 14(4), 1203; https://doi.org/10.3390/en14041203 - 23 Feb 2021

Cited by 9 | Viewed by 2857

Abstract

Modern electric vehicle heating, ventilation, and air-conditioning (HVAC) systems operate in more efficient heat pump mode, thus, improving the driving range under cold ambient conditions. Coupling those HVAC systems with novel heating technologies such as infrared heating panels (IRP) results in a complex [...] Read more.

Modern electric vehicle heating, ventilation, and air-conditioning (HVAC) systems operate in more efficient heat pump mode, thus, improving the driving range under cold ambient conditions. Coupling those HVAC systems with novel heating technologies such as infrared heating panels (IRP) results in a complex system with multiple actuators, which needs to be optimally coordinated to maximise the efficiency and comfort. The paper presents a multi-objective genetic algorithm-based control input allocation method, which relies on a multi-physical HVAC model and a CFD-evaluated cabin airflow distribution model implemented in Dymola. The considered control inputs include the cabin inlet air temperature, blower and radiator fan air mass flows, secondary coolant loop pump speeds, and IRP control settings. The optimisation objective is to minimise total electric power consumption and thermal comfort described by predictive mean vote (PMV) index. Optimisation results indicate that HVAC and IRP controls are effectively decoupled, and that a significant reduction of power consumption (typically from 20% to 30%) can be achieved using IRPs while maintaining the same level of thermal comfort. The previously proposed hierarchical HVAC control strategy is parameterised and extended with a PMV-based controller acting via IRP control inputs. The performance is verified through simulations in a heat-up scenario, and the power consumption reduction potential is analysed for different cabin air temperature setpoints. Full article

(This article belongs to the Special Issue Energy Efficient Cooling and Heating Systems for Improved Passenger Thermal Comfort in Electric Vehicles)

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17 pages, 5813 KiB

Open AccessArticle

PCM-Based Energy Storage System with High Power Output Using Open Porous Aluminum Foams

by Joachim Baumeister, Jörg Weise, Sebastian Myslicki, Esther Kieseritzky and Götz Lindenberg

Energies 2020, 13(23), 6198; https://doi.org/10.3390/en13236198 - 25 Nov 2020

Cited by 12 | Viewed by 2318

Abstract

Thermal comfort (heating, ventilation and air conditioning, HVAC) and the energy consumption involved with it can put a strain on the driving range of fully electric vehicles (FEV), especially in certain times of the year as midsummer or winter. In order to reduce [...] Read more.

Thermal comfort (heating, ventilation and air conditioning, HVAC) and the energy consumption involved with it can put a strain on the driving range of fully electric vehicles (FEV), especially in certain times of the year as midsummer or winter. In order to reduce the energy consumption of HVAC, improved thermal management and adapted means of energy storage are needed. One part of the solution can be the use of phase change materials (PCM) for storing waste heat. For the specific application, however, a high loading/unloading power rate is required, which is challenging as the PCMs exhibit low heat conductivities. In the presented work, a storage demonstrator system was investigated which is part of an HVAC system of a specific fully electric vehicle. The profile of requirements of the system (power, stored capacity and allowed volume) make a new design of the storage necessary. Two demonstrator units, in which the PCM was combined with aluminum foam, were manufactured and their power output in dependency on the fluid flow of the coolant system was compared. An adapted squeeze casting process with polymer placeholders was used for the production of the aluminium foam. This process results in foams with a specific pore structure and allows the in-situ integration of the heat transfer fluid (HTF) pipes. Both newly developed PCM storage systems satisfy the HVAC system requirements. Full article

(This article belongs to the Special Issue Energy Efficient Cooling and Heating Systems for Improved Passenger Thermal Comfort in Electric Vehicles)

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18 pages, 6825 KiB

Open AccessArticle

Demand-Based Control Design for Efficient Heat Pump Operation of Electric Vehicles

by Dominik Dvorak, Daniele Basciotti and Imre Gellai

Energies 2020, 13(20), 5440; https://doi.org/10.3390/en13205440 - 19 Oct 2020

Cited by 12 | Viewed by 2242

Abstract

Thermal management systems of passenger vehicles are fundamental to provide adequate cabin thermal comfort. However, for battery electric vehicles they can use a significant amount of battery energy and thus reduce the real driving range. Indeed, when heating or cooling the vehicle cabin [...] Read more.

Thermal management systems of passenger vehicles are fundamental to provide adequate cabin thermal comfort. However, for battery electric vehicles they can use a significant amount of battery energy and thus reduce the real driving range. Indeed, when heating or cooling the vehicle cabin the thermal management system can consume up to 84% of the battery capacity. This study proposes a model-based approach to design an energy-efficient control strategy for heating electric vehicles, considering the entire climate control system at different ambient conditions. Specifically, the study aims at reducing the energy demand of the compressor and water pumps when operating in heat pump mode. At this scope, the climate control system of the reference vehicle is modelled and validated, enabling a system efficiency analysis in different operating points. Based on the system performance assessment, the optimized operating strategy for the compressor and the water pumps is elaborated and the results show that the demand-based control achieves up to 34% energy reduction when compared to the standard control. Full article

(This article belongs to the Special Issue Energy Efficient Cooling and Heating Systems for Improved Passenger Thermal Comfort in Electric Vehicles)

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23 pages, 7174 KiB

Open AccessArticle

Optimisation of Control Input Allocation Maps for Electric Vehicle Heat Pump-based Cabin Heating Systems

by Ivan Cvok, Igor Ratković and Joško Deur

Energies 2020, 13(19), 5131; https://doi.org/10.3390/en13195131 - 02 Oct 2020

Cited by 8 | Viewed by 3001

Abstract

The heating, ventilation and air conditioning (HVAC) system negatively affects the electric vehicle (EV) driving range, especially under cold ambient conditions. Modern HVAC systems based on the vapour-compression cycle can be rearranged to operate in the heat pump mode to improve the overall [...] Read more.

The heating, ventilation and air conditioning (HVAC) system negatively affects the electric vehicle (EV) driving range, especially under cold ambient conditions. Modern HVAC systems based on the vapour-compression cycle can be rearranged to operate in the heat pump mode to improve the overall system efficiency compared to conventional electrical/resistive heaters. Since such an HVAC system is typically equipped with multiple actuators (compressor, pumps, fans, valves), with the majority of them being controlled in open loop, an optimisation-based control input allocation is necessary to achieve the highest efficiency. This paper presents a genetic algorithm optimisation-based HVAC control input allocation method, which utilises a multi-physical HVAC system model implemented in Dymola/Modelica. The considered control inputs include the cabin inlet air temperature reference, blower and radiator fan air mass flows and secondary coolant loop pumps’ speeds. The optimal allocation is subject to specified, target cabin air temperatures and heating power. Additional constraints include actuator hardware limits and safety functions, such as maintaining the superheat temperature at its reference level. The optimisation objective is to maximise the system efficiency defined by the coefficient of performance (COP). The optimised allocation maps are fitted by proper mathematical functions to facilitate the control strategy implementation and calibration. The overall control strategy consists of superimposed cabin air temperature controller that commands heating power, control input allocation functions, and low-level controllers that ensure cabin inlet air and superheat temperature regulation. The control system performance is verified through Dymola simulations for the heat pump mode in a heat-up scenario. Control input allocation map optimisation results are presented for air-conditioning (A/C) mode, as well. Full article

(This article belongs to the Special Issue Energy Efficient Cooling and Heating Systems for Improved Passenger Thermal Comfort in Electric Vehicles)

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31 pages, 5089 KiB

Open AccessArticle

Optimal Management of Thermal Comfort and Driving Range in Electric Vehicles

by Anas Lahlou, Florence Ossart, Emmanuel Boudard, Francis Roy and Mohamed Bakhouya

Energies 2020, 13(17), 4471; https://doi.org/10.3390/en13174471 - 31 Aug 2020

Cited by 19 | Viewed by 2512

Abstract

The HVAC system represents the main auxiliary load in battery-powered electric vehicles (BEVs) and requires efficient control approaches that balance energy saving and thermal comfort. On the one hand, passengers always demand more comfort, but on the other hand the HVAC system consumption [...] Read more.

The HVAC system represents the main auxiliary load in battery-powered electric vehicles (BEVs) and requires efficient control approaches that balance energy saving and thermal comfort. On the one hand, passengers always demand more comfort, but on the other hand the HVAC system consumption strongly impacts the vehicle’s driving range, which constitutes a major concern in BEVs. In this paper, a thermal comfort management approach that optimizes the thermal comfort while preserving the driving range during a trip is proposed. The electric vehicle is first modeled together with the HVAC and the passengers’ thermo-physiological behavior. Then, the thermal comfort management issue is formulated as an optimization problem solved by dynamic programing. Two representative test-cases of hot climates and traffic situations are simulated. In the first one, the energetic cost and ratio of improved comfort is quantified for different meteorological and traffic conditions. The second one highlights the traffic situation in which a trade-off between the driving speed and thermal comfort is important. A large number of weather and traffic situations are simulated and results show the efficiency of the proposed approach in minimizing energy consumption while maintaining a good comfort. Full article

(This article belongs to the Special Issue Energy Efficient Cooling and Heating Systems for Improved Passenger Thermal Comfort in Electric Vehicles)

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22 pages, 5116 KiB

Open AccessArticle

A Real-Time Approach for Thermal Comfort Management in Electric Vehicles

by Anas Lahlou, Florence Ossart, Emmanuel Boudard, Francis Roy and Mohamed Bakhouya

Energies 2020, 13(15), 4006; https://doi.org/10.3390/en13154006 - 03 Aug 2020

Cited by 11 | Viewed by 2214

Abstract

The HVAC system represents the main auxiliary load in electric vehicles, but passengers’ thermal comfort expectations are always increasing. Hence, a compromise is needed between energy consumption and thermal comfort. The present paper proposes a real-time thermal comfort management strategy that adapts the [...] Read more.

The HVAC system represents the main auxiliary load in electric vehicles, but passengers’ thermal comfort expectations are always increasing. Hence, a compromise is needed between energy consumption and thermal comfort. The present paper proposes a real-time thermal comfort management strategy that adapts the thermal comfort according to the energy available for operating the HVAC system. The thermal comfort is evaluated thanks to the “Predicted Mean Vote”, representative of passenger’s thermal sensations. Based on traffic and weather predictions for a given trip, the algorithm first estimates the energy required for the traction and the energy available for thermal comfort. Then, it determines the best thermal comfort that can be provided in these energetic conditions and controls the HVAC system accordingly. The algorithm is tested for a wide variety of meteorological and traffic scenarios. Results show that the energy estimators have a good accuracy. The absolute relative error is about 1.7% for the first one (traction), and almost 4.1% for the second one (thermal comfort). The effectiveness of the proposed thermal comfort management strategy is assessed by comparing it to an off-line optimal control approach based on dynamic programming. Simulation results show that the proposed approach is near-optimal, with a slight increase of discomfort by only 3%. Full article

(This article belongs to the Special Issue Energy Efficient Cooling and Heating Systems for Improved Passenger Thermal Comfort in Electric Vehicles)

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16 pages, 3751 KiB

Open AccessArticle

A Novel Methodology for Evaluating the Impact of Energy Efficiency Measures on the Cabin Thermal Comfort of Electric Vehicles

by Daniele Basciotti, Dominik Dvorak and Imre Gellai

Energies 2020, 13(15), 3872; https://doi.org/10.3390/en13153872 - 29 Jul 2020

Cited by 9 | Viewed by 2643

Abstract

Climate control systems have a largely negative effect on the energy consumption of electric vehicles and consequently on their real driving range. Improving the efficiency of climate control systems requires advanced simulation tools for an accurate evaluation of both the energy savings and [...] Read more.

Climate control systems have a largely negative effect on the energy consumption of electric vehicles and consequently on their real driving range. Improving the efficiency of climate control systems requires advanced simulation tools for an accurate evaluation of both the energy savings and thermal comfort of innovative heating and cooling solutions. In this study, the advancements beyond the state of the art consists primarily of the methodology tackling the reduction of computational costs of intensive computational fluid dynamics (CFD) simulations and/or time-consuming experimental investigations and the simultaneous assessment of vehicle cabin thermal comfort and energy flows. The approach was validated against climatized chassis dyno measurements from the EU Horizon 2020 research project QUIET. Indeed, all the considered locations within the cabin were properly validated, both in steady state and transient conditions with the largest deviations at steady state below 3 °C. Additionally, the validation results show a perfect agreement for the average cabin predicted mean vote (PMV) value and a largest deviation in terms of the PMV for the other locations below 0.3. Furthermore, the applicability of the methodology is proved with the help of its application on a parametric study for which various cabin temperature setpoints and heating, ventilation and air conditioning (HVAC) modes were simulated in winter operation. Full article

(This article belongs to the Special Issue Energy Efficient Cooling and Heating Systems for Improved Passenger Thermal Comfort in Electric Vehicles)

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Review

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0 pages, 594 KiB

Open AccessReview

A Review of the Integrated Design and Control of Electrified Vehicles

by Caiyang Wei, Theo Hofman, Esin Ilhan Caarls and Rokus van Iperen

Energies 2020, 13(20), 5454; https://doi.org/10.3390/en13205454 - 19 Oct 2020

Cited by 17 | Viewed by 3107

Abstract

From a control perspective, the energy management system and the thermal management system of an electrified vehicle are often developed separately, which may not yield the optimal solution. Moreover, an optimal system design requires concurrent plant (topology and size) and controller optimization, which [...] Read more.

From a control perspective, the energy management system and the thermal management system of an electrified vehicle are often developed separately, which may not yield the optimal solution. Moreover, an optimal system design requires concurrent plant (topology and size) and controller optimization, which should apply to both energy and thermal domains. This paper originally provides a comprehensive analysis of design and control optimization layers to reveal the interconnections between them and how they influence the optimality of an electrified vehicle design considering both energy and thermal domains. It was found that energy and cost savings can be achieved by integrating these optimization layers, and the energy and thermal domains with four coordination schemes, namely, sequential, iterative, nested and simultaneous. There is a trade-off between optimality, causality, complexity and computational time. Additionally, future research directions in terms of reducing energy consumption and system costs of electrified vehicles are identified herein, such as using integrated design and control methods, employing electrified actuators, exchanging heat between powertrain components and utilizing waste heat recovery systems. Full article

(This article belongs to the Special Issue Energy Efficient Cooling and Heating Systems for Improved Passenger Thermal Comfort in Electric Vehicles)

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