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

Lahlou, Anas; Ossart, Florence; Boudard, Emmanuel; Roy, Francis; Bakhouya, Mohamed

doi:10.3390/en13154006

Cited by 17 publications

(9 citation statements)

References 21 publications

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“…Actuality, the energy consumption of HVAC is calculated by the performance compression curve of the compressor and the change in enthalpy actuality. To simplify the calculation, the study approximates that energy consumption is inversely proportional to the HVAC outlet airflow temperature T ac [ 18 ]. High energy consumption would reduce users’ satisfaction.…”

Section: Methodsmentioning

confidence: 99%

Environmental conditions driven method for automobile cabin pre-conditioning with multi-satisfaction objectives

Chen

Lan

2022

PLoS ONE

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The optimal initial pre-conditioning parameter is essential to properly adjust the temperature within the cabin in an effective and accurate way, especially while passengers’ thermal comfort and energy-saving properties are both considered. Under the various environmental thermal loads, the pre-conditioning solutions resulting from those pre-fixed cooling parameters are unfeasible for achieving accurately passengers’ comfort temperature. In addition, it is also difficult in such a narrow car space to identify a lot of local attributes due to the different material properties and sizes of a variety of structural parts that have various thermal responses to environmental conditions. This paper presents a data-driven decision model to numerically identify the degrees of the cabin thermal characteristic to determine satisfactory pre-conditioning parameter schemes. Initially, based on the thermal data within a vehicle recorded through the whole year at a selected hot climate region of the Middle East, the study levels multiple climate scenes corresponding to change in the cabin air temperature. Then three classification algorithms (Support Vector Machines, Decision Tree, and K-nearest neighbor model) are used to comparatively identify climate levels according to the input conditions. Based on the identified climate level, an appropriate parameters scheme for this level is applied. A comprehensive evaluation index (CEI) is proposed to characterize the passengers’ satisfaction in numerical computation, on considering multi-satisfaction objectives including Predicted Mean Vote (PMV), local temperature, air quality, and energy efficiency; and it formulates the pre-conditioning parameter scheme for each climate scene with CEI. Several scene cases are carried out to verify the effectiveness of the proposed models. The result shows that the pre-conditioning schemes of the model can effectively satisfy passengers in multi-satisfaction objectives.

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Section: Methodsmentioning

confidence: 99%

Environmental conditions driven method for automobile cabin pre-conditioning with multi-satisfaction objectives

Chen

Lan

2022

PLoS ONE

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“…As a further improvement with respect to an optimal control approach explored by Lahlou et al in [35], a connected BEV, having set a defined road trip in the GPS navigation aid system and knowing the traffic level and the environmental conditions, could estimate in real time the energy needed for traction and the energy available for regulating the thermal comfort. This possibility was simulated by the author in [36] for different traffic and weather condition scenarios, and different initial battery states of charge.…”

Section: • Advanced Thermal Storagementioning

confidence: 99%

Assessing the Energy Consumption and Driving Range of the QUIET Project Demonstrator Vehicle

et al. 2022

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This article summarises the experimental testing campaign performed at the Joint Research Centre (JRC) on the demonstrator battery electric vehicle (BEV) of the European Union Horizon 2020 research project QUIET. The project, launched in October 2017, aimed at developing an improved and energy-efficient electric vehicle with increased driving range under real-world driving conditions, focusing on three areas: improved energy management, lightweight materials with enhanced thermal insulation properties, and improved safety and comfort. A heating, venting, and air conditioning (HVAC) system based on the refrigerant R290 (propane), a phase change material (PCM) thermal storage system, infrared heating panels in the near field of the passengers, lightweight materials for seat internal structures, and composite vehicle doors with a novel atomically precise manufacturing (APM) aluminium foam are all the breakthrough technologies installed on the QUIET demonstrator vehicle. All these innovative technologies allow the energetic request for cooling and heating the cabin of the demonstrator vehicle under different driving conditions and the weight of the vehicle components (e.g., doors, windshields, seats, heating, and air conditioning) to be reduced by about 28%, leading to an approximately 26% driving range increase under both hot (40 °C) and cold (−10 °C) weather conditions.

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“…Methods of evaluating and improving the energy efficiency of vehicles are divided into two groups. The first includes methods and technologies aimed at achieving the goal by improving the structural properties of new cars [3][4][5][6][7]. Thus, the author [3] proposed a complex indicator of car energy efficiency, which is used to justify and implement a complex of technical and technological innovations based on the model of the modular structural and parametric organization of the design of a new car.…”

Section: Analysis Of Latest Research and Publicationsmentioning

confidence: 99%

Evaluation of transport system configuration by efficiency indicators

Mateichyk¹,

Śmieszek²,

Kostian³

2022

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The study is devoted to the process of evaluating the efficiency of the transport system in terms of urban mobility. The approach is based on the use of a system of performance indicators using neurocomputer technologies. Generalized models for obtaining a vector of performance indicators and an integral performance indicator in the form of computer neural networks are proposed. It is shown that to record the fact that the indicator values fall to the threshold and below, it is enough to use a neural network built on perceptron neurons. The multi-layered model for determining the integral indicator allows assessing the importance of individual indicators in the system of monitoring the efficiency of a given configuration of the transport system. An experimental study of twenty-five states of the transport system of various configurations in the cities of Poland and Ukraine was carried out. The key indicators of the system's efficiency are determined, namely, the energy efficiency indicator of the vehicle as a system element, the environmental indicator and the traffic safety indicator. Based on the results of the experimental study, a neural network structure is proposed for evaluating the energy efficiency of given configurations of the transport system. For the purpose of training and testing the obtained network, the procedure of adjusting the threshold value of the activation function and normalizing the values of the input parameters array of the transport system was used. The constructed network was implemented using Visual Studio 2019 using the C++ language. The network was adjusted to determine the energy efficiency estimate with a given accuracy by replacing the perceptron neuron with a regular one with a sigmoidal activation function. The random nature of the choice of the configuration and the initial values of the weighting factors made it possible to obtain a model with an accuracy of implementation on the control sample in the range from 90 to 98.7% at a learning rate of 0.1.

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

Cited by 17 publications

References 21 publications

Environmental conditions driven method for automobile cabin pre-conditioning with multi-satisfaction objectives

Environmental conditions driven method for automobile cabin pre-conditioning with multi-satisfaction objectives

Assessing the Energy Consumption and Driving Range of the QUIET Project Demonstrator Vehicle

Evaluation of transport system configuration by efficiency indicators

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