Electric Vehicle Thermal Management Research Articles

A two-stage eco-cooling control strategy for electric vehicle thermal management system considering multi-source information fusion

A two-stage eco-cooling control strategy for electric vehicle thermal management system considering multi-source information fusion

Thermal Management in Electric Vehicles: Modeling and Prospects

Thermal Management in Electric Vehicles: Modeling and Prospects

Co-regulation of integrated thermal management based on refrigerant cooling for electric vehicles

As an essential part of an electric vehicle thermal management system, collaborative regulation of power battery thermal management and AC temperature is imperative to maximize the vehicle's driving range and energy utilization effectiveness. This work proposes a joint control pattern for the compressor (Com) and variable opening valves (VOVs) with a dual-evaporator system. Specifically, the compressor rotation speed is the dominant control variable, and the battery's thermal behavior and system COP are investigated. The analytic results demonstrate that when the system is under moderate and high thermal loads, the Com-VOVB-VOVC strategy can regulate the temperature of both the battery and AC temperature. Meanwhile, the goal of low energy consumption is optimized. Nevertheless, when the thermal load is low, the Com-VOVB strategy can attain steady temperature regulation for the dual-evaporator and decrease the complexity of the system control. In addition, a Map approach to the temperature regulation is presented, enhancing the effectiveness and dynamism of thermal management control. The common control method for an integrated thermal management system can effectively confront system thermal load changes and decrease energy consumption.

The Collaborative Optimization of the Discharge Pressure and Heat Recovery Rate in a Transcritical CO2 Heat Pump Used in Extremely Low Temperature Environment

Considering the excellent environmental properties and heating capability under wide running conditions of the natural fluid CO2, the transcritical CO2 heat pump system has widely been used in the application of water heaters, commercial heating and cooling, electric vehicle thermal management, etc. Since the performance was highly affected by the discharge pressure and heat recovery rate in a transcritical CO2 system, the collaborative optimization of these two parameters was analyzed in detail in this study. The results showed that the optimal value of the system heating COP, which was the ration of heating capacity to power consumption, was better under a higher heat recovery rate and relatively lower discharge pressure, which is why these kinds of operating conditions are highly recommended from the perspective of collaborative optimization. Additionally, the heat recovery rate had a positive effect on the system performance when the discharge pressure was lower than its optimal value, while the heat recovery rate would present a passive effect on the system performance when the discharge pressure was higher than its optimal value. The relevant conclusions of this study provide a good theoretical basis for the efficient and stable operation of the transcritical CO2 heat pump technology under the conditions of a wide ambient temperature range.

Heat load estimation and thermodynamic analysis of the thermal management of an electric car

Thermal management of electric vehicles is a key step in their wide spread and safe usage. This work considers an electric car as a combination of three entities which contribute to the thermal load viz. the battery, motor and passenger cabin. A refrigerant based cooling system is proposed and is applied to a mid-size electric car (∼60 kW) to obtain the heat load, sizing of the components and the performance analysis based on the 1st and 2nd laws of thermodynamics. At nominal operating conditions, the battery offers a heat load of 3.3 kW, motor of 3.25 kW and cabin of 4.53 kW. However, at adverse operating conditions, the battery offers a heat load of 4 kW, motor of 3 kW and cabin of 3 kW. The proposed cooling system successfully evacuates the heat and manages the temperature of the electric vehicle. The exergy destruction at different ambient conditions also is studied and is found to increase at higher ambient temperatures. Compressor is found to be carrying out the maximum exergy destruction.

Parametric study on thermal management system for the range of full (Tesla Model S)/ compact-size (Tesla Model 3) electric vehicles

Electric vehicle is slowly taking over the market share of internal combustion engine vehicle around the globe and range extension study turns into a one key research area. Electric vehicle thermal management system plays a large role in driving range, whereas existing literature mainly focus on component level and lack the vehicle level range analysis. This study conducts a parametric study on the vehicle level thermal management and its impacts on the range of two vehicles (full size - Tesla Model S/ compact size – Tesla Model 3). Vehicle level thermal system model is built considering air conditioning refrigerant loop, indirect battery liquid cooling loop, and cabin cooling air loop. In addition, vehicle propulsion system model is built and utilized in the range simulation. Five feedback controllers are designed for the thermal management system to control the temperature of battery pack, cabin climate, condenser subcool, evaporator superheat, and chiller superheat. Various factors are considered in the parametric study including air conditioning system on/off switch, vehicle size, driving cycle, ambient temperature, cabin target temperature, and battery pack target temperature. In the results analysis, the performance of five feedback controllers is evaluated in step response and a driving cycle. Energy consumption of aerodynamic drag, rolling resistance, thermal management, regenerative braking, and auxiliary load are discussed in the parametric study. The results show that turning air conditioning system on could potentially reduce the EV range by 38–45 % at city driving condition. In addition, Ambient temperature shows significant nonlinear impact on EV range and the impact gets worse as temperature turns higher. For Tesla Model 3, when the ambient temperature rises from 30 °C to 35 °C and then to 40 °C, the range drops by 3.3 % and 13.4 %, respectively. Compared with ambient temperature, cabin temperature and battery pack temperature settings have less impact on the range. The code utilized in this study is made open source via Github (https://github.com/binxuAI/EV_TMS), which can be utilized as the guidance in the thermal management range impact analysis and concept design of electric vehicle.

NUMERICAL STUDY OF THE PERFORMANCE OF HEAT PIPE-BASED THERMAL MANAGEMENT SYSTEM FOR POWER LITHIUM BATTERY

The power battery thermal management system (BTMS) is a key component of an electric vehicle (EV) thermal management system. In this paper, a novel heat pipe-based temperature control system for power batteries is devised for a cylindrical battery pack. In this system, the battery is wrapped in an aluminum sleeve with heat pipes attached to the outside, and heat is removed from the heat pipe's evaporative end by the coolant. Effects of four different arrangements of heat pipes on the thermal properties of BTMS under different inlet flow conditions are studied numerically. The results show that when the flow rate reaches a certain value, the temperature of the battery module no longer decreases and even rises. Finally, based on the comprehensive consideration of energy consumption and cooling performance, the optimal heat pipe arrangement is concluded for the battery in different discharge rate scenarios. In conclusion, the cooling method of heat pipe plus liquid cooling can effectively control the battery temperature, and the temperature homogeneity of the system can be well improved by adjusting the position of the heat pipe arrangement. When the cell heat generation is 0.65 W/cell, the overall temperature difference of the battery pack is reduced by 15% by optimizing the heat pipe arrangement, and when the cell heat generation is 2 W/cell, the overall temperature difference is reduced by 19%.

A Computationally Efficient Algorithm for Perturbed Dynamic Programs (A-PDP)

This letter proposes an algorithm for solving perturbed dynamic programs, where first-order corrections are applied to a pre-computed optimal strategy and its corresponding value function using local quadratic approximation. The technique is developed to handle perturbations of external inputs and parameters affecting system dynamics, objective and constraint functions, allowing the application to a wide variety of perturbed problems. The method is applied to the energy optimization of an electric vehicle thermal management system, formulated as a constrained dynamic program where external conditions and target set-point are perturbed from their nominal values. Simulations result show 80% reduction in computation time from a Dynamic Programming (DP) solution, with only minimal effect on the overall controller performance.

Performance optimization of electric vehicle battery thermal management based on the transcritical CO2 system

Thermal management of electric vehicles, especially battery thermal management, is critical to driving range and operational safety. To find a vehicle thermal management system with higher energy efficiency and environmental protection, an environmentally-friendly and efficient battery and cabin parallel cooling thermal management system was evaluated with CO2 as the working fluid. First, different control strategies of the evaporation temperature were compared regarding the battery cooling performance. Then, the effect of the battery cooling evaporation temperature on the coefficient of performance (COP) was explored. It was found that the maximum COP increased by 8.38% as the evaporation temperature decreased from 17 to 5.8 °C. Besides, it was found that the optimal battery cooling evaporation temperature range is 10.2–11 °C when the battery heating power is 0.4 kW. The vapor quality at the cold plate outlet should be lower than 0.95. Finally, the battery cooling performance under variable operating conditions was investigated. The influence of operating parameters on the battery cooling evaporation temperature and CO2 outlet vapor quality was also analyzed. Simulation results showed that the optimum evaporation temperature range varied significantly under different working conditions. The vapor quality at the cold plate outlet decreased slightly with the evaporation temperature.

Review on Battery Packing Design Strategies for Superior Thermal Management in Electric Vehicles

In the last decades of electric vehicle (EV) development, battery thermal management has become one of the remaining issues that must be appropriately handled to ensure robust EV design. Starting from researching safer and more durable battery cells that can resist thermal exposure, battery packing design has also become important to avoid thermal events causing an explosion or at least to prevent fatal loss if the explosion occurs. An optimal battery packing design can maintain the battery cell temperature at the most favorable range, i.e., 25–40 °C, with a temperature difference in each battery cell of 5 °C at the maximum, which is considered the best working temperature. The design must also consider environmental temperature and humidity effects. Many design strategies have been reported, including novel battery pack constructions, a better selection of coolant materials, and a robust battery management system. However, those endeavors are faced with the main challenges in terms of design constraints that must be fulfilled, such as material and manufacturing costs, limited available battery space and weight, and low energy consumption requirements. This work reviewed and analyzed the recent progress and current state-of-the-art in designing battery packs for superior thermal management. The narration focused on significant findings that have solved the battery thermal management design problem as well as the remaining issues and opportunities to obtain more reliable and enduring batteries for EVs. Furthermore, some recommendations for future research topics supporting the advancement of battery thermal management design were also discussed.

Control strategy research of electric vehicle thermal management system based on MGA-SVR algorithm

The thermal management system is one of the important assemblies that ensure the secure operation of electric vehicles (EVs). Using intelligent algorithms to optimize the control strategy of the thermal management system can reduce energy consumption under the premise of effective heat dissipation of EVs. This paper attempts to construct the control strategy of EV thermal management system by coupling the modified genetic algorithm (MGA) and support vector regression (SVR). Firstly, the double-population adaptive mutation method and a novel optimization process are adopted to obtain MGA. Afterward, the performance of MGA is verified by four benchmark functions compared with three typical algorithms, which are genetic algorithm (GA), double-population genetic algorithm (DPGA), and quantum genetic algorithm (QGA). The results demonstrate that the accuracy and stability of MGA are obviously better than the other three algorithms. Secondly, MGA is applied to modify parameters of SVR kernel function, and the accuracy of MGA-SVR algorithm is verified by the Auto-MPG and Computer Hardware data sets. The mean square deviations of the SVR algorithm test set are 0.0186 and 0.0806, respectively, and the mean square deviations of the MGA-SVR algorithm test set are 0.0099 and 0.0054, respectively, which fully shows that MGA-SVR have more accurate forecasting capabilities. Finally, the thermal management system model of EV is built by the one-dimensional simulation software KULI. Under the Chinese working condition, fan speed which meets the cooling requirements of the motor and controller is obtained from the KULI model, and the database is constructed. Then, MGA-SVR is trained by database and employed to predict fan speed under the Chinese working condition and obtain control strategy of the thermal management system. Compared with traditional control strategy, the thermal management system based on MGA-SVR control strategy can not only meet the radiating requirements, but also effectively reduce the power consumption of fans.

An Optimization Study on the Operating Parameters of Liquid Cold Plate for Battery Thermal Management of Electric Vehicles

The development of electric vehicles plays an important role in the field of energy conservation and emission reduction. It is necessary to improve the thermal performance of battery modules in electric vehicles and reduce the power consumption of the battery thermal management system (BTMS). In this study, the heat transfer and flow resistance performance of liquid cold plates with serpentine channels were numerically investigated and optimized. Flow rate (m˙), inlet temperature (Tin), and average heat generation (Q) were selected as key operating parameters, while average temperature (Tave), maximum temperature difference (ΔTmax), and pressure drop (ΔP) were chosen as objective functions. The Response Surface Methodology (RSM) with a face-centered central composite design (CCD) was used to construct regression models. Combined with the multi-objective non-dominated sorting genetic algorithm (NSGA-II), the Pareto-optimal solution was obtained to optimize the operation parameters. The results show that the maximum temperature differences of the cold plate can be controlled within 0.29~3.90 °C, 1.11~15.66 °C, 2.17~31.39 °C, and 3.43~50.92 °C for the discharging rates at 1.0 C, 2.0 C, 3.0 C, and 4.0 C, respectively. The average temperature and maximum temperature difference can be simultaneously optimized by maintaining the pressure drop below 1000 Pa. It is expected that the proposed methods and results can provide theoretical guidance for developing an operational strategy for the BTMS.

Fuel cell plug-in hybrid electric vehicle thermal management strategy in parking time for low-temperature environments

This work presents a thermal management strategy for fuel cell hybrid electric vehicles under low-temperature conditions. Protecting the fuel cell system (FCS) and battery pack from such operating conditions prevent their degradation and performance decay. Thus, an approach similar to the keep-warm strategy is proposed to avoid the well-known issues related to the thaw-at-start methods, as well as promote a rapid startup after long parking periods. Particularly, the present work proposes a strategic synergy between the battery pack recharging and thermal management during the parking phase, so as to minimize the fuel consumption, while featuring vehicle to grid functionality and rapid startup of the vehicle when resuming driving. Such thermal management strategy was evaluated via simulation analyses, considering the transient thermal dynamics of the FCS and battery pack under low-temperature conditions and the temperature control strategy. The results outlined how proper exploitation of plugin functionalities, beyond introducing innovative vehicle-to-grid (V2G) concepts to suitably link driving to parking phases energy management, also allows for low-temperature safe thermal management of involved electrochemical devices. Finally, an economic analysis demonstrated that the proposed plugin-based vehicle to grid scenario presents a cost-saving potential of up to 56 % with respect to non V2G charge-sustaining one.

Innovative HMI and Control Concept for Efficient Thermal Management of Electric Vehicles

This study presents a practical design and implementation of a Thermal Management (TM) concept for Battery-Electric Vehicles (BEVs) including a novel Human-Machine Interface (HMI). The developed system uses a combination of convective air conditioning and radiation heating to cool down and heat up the passengers efficiently. The proposed contribution can be subdivided into four parts: 1) description of the Heating, Ventilation and Air Conditioning (HVAC) system; 2) development of a novel HMI; 3) derivation of an appropriate operating strategy concept; 4) validation of the entire TM system based on a user study using a demonstrator vehicle. The results show that the developed TM concept can substantially support the user to operate the HVAC system more efficiently. A user study was conducted to evaluate passenger comfort and usability. The study revealed that users tend to operate a conventional input panel of an HVAC system inefficiently in some cases. They could achieve better task performance with the new HMI proposed in this study. However, the acceptance of the new concept was rated lower for the new system, as users were already accustomed to the conventional input panel design.

Unified Thermal System Simulations of an Electric Truck

<div class="section abstract"><div class="htmlview paragraph">Effective thermal management of an EV becomes a complex and yet essential topic due to strong dependence of electric powertrain performance on the thermal system performance. Once the powertrain sizing is decided for any new EV, electric vehicle thermal management is major challenge and opportunity to improve on overall energy efficiency. This is more pertinent in the context of a commercial vehicle where range is of utmost importance. A novel approach is proposed hereby to integrate different interfacing systems & subsystems of a vehicle that play a critical role for determination of thermal system sizing. This includes starting from vehicle model, electric powertrain (ePT) HVAC and cooling systems and simulate these in one environment under different scenarios as per customer expectations. A simplified controller is designed and integrated to monitor and control the functioning of such thermal systems for <span class="strike-through">desired</span> performance.</div><div class="htmlview paragraph">Transient simulations are performed to mimic real world routes to analyze and select right under-hood module over a range of different ambient conditions. Commercial software namely GT is used for flow and thermal modelling and Simulink is used for power electric models and controller. Iterative process is established to arrive at right combination of radiators, fan, pump and compressor size along with optimum controller actuation to regulate the events of heat exchange meeting all thermal marginal limits of Battery & PE loop components. The method is being extended to evaluate different thermal concepts through different thermal architecture.</div></div>

Pseudo-optimal discharge pressure analysis of transcritical CO2 electric vehicle heat pumps due to temperature glide

• A pseudo-optimal discharge pressure for electric vehicle heat pumps was proposed. • The principle of pseudo-optimal discharge pressure was explained. • Pseudo-optimal discharge pressure exists in subcritical and transcritical states. • The effects of conditions on pseudo-optimal discharge pressures were revealed. Performance improvement of electric vehicle heat pumps can enhance thermal comfort and reduce the power consumption of electric vehicles, hence stimulating their development. In this paper, the cyclic characteristics of an electric vehicle heat pump were studied under different operating modes and working conditions. Different from the optimal discharge pressure of conventional CO 2 systems which was determined by the variation gradient characteristics of the transcritical isotherm, the discharge pressure of electric vehicle heat pumps at the peak COP value was defined as a pseudo-optimal discharge pressure and was determined by the obvious temperature glide at the outlet of the gas cooler. This pseudo-optimal discharge pressure existed at both transcritical and subcritical states. The difference in the pseudo-optimal discharge pressure between the subcritical or transcritical states was first evaluated. Then an in-depth analysis of the influence of key parameters on the pseudo-optimal discharge pressure was studied to develop an accurate prediction method since the traditional prediction methods were not applicable. The results showed that pseudo-optimal discharge pressure increased with the ambient temperature, inlet air temperature, and supply air temperature. This study provides valuable information for the comprehensive performance optimization of an electric vehicle thermal management system.

Research on liquid preheating performance for battery thermal management of electric vehicles at low temperature

The discharge efficiency of electric vehicles in extremely cold temperatures (−40 °C to −20 °C) is greatly reduced, and it often takes a lot of time to warm up the battery when starting. Therefore, the purpose of this study is to rapidly warm up the battery at cold temperatures. In order to judge whether it is rapid preheating, we set 180 s (3 min) as the standard value for the duration of rapid preheating of the battery. We designed six hollow aluminum plates to fit on the sides of the five batteries, and heat transfer fluid (HTF) flows through the hollow aluminum plates to bring heat to the batteries. A three-dimensional computational fluid dynamics (CFD) system was established. By studying the three important parameters of pipe diameter, flow rate, and HTF temperature, it was found that the pipe diameter had no significant effect on battery preheating, and should be selected in conjunction with the flow rate. If the battery is preheated to a temperature of 25 °C, the HTF should be higher than 25 °C. But the higher the HFT temperature, the greater the temperature difference between the battery packs. The preheating is completed within 180 s, and the optimum temperature of HTF is 30 °C.

Performance analysis of an integrated battery electric vehicle thermal management

Fast introducing battery electric vehicles to the market leads to the accumulation of errors and recalls of the vehicle. It can be avoided by simulating battery electric vehicles (BEV) in an integrated manner. A drivetrain model is developed integrated with cabin, battery, and power electronics models. Key system-level outputs like vehicle energy consumption, system COP, and total auxiliary power are obtained, and component-level outputs include internal battery temperature, power electronics temperature, and cabin temperatures. The integrated model is validated both at the component level and system level. Simple energy-conscious actions are identified, and corresponding energy savings are quantified over the lifetime of a battery-electric vehicle. Simple energy-conscious actions can save 1336 to 4297 kWh of energy throughout the vehicle's lifetime. When the ambient temperature is doubled from 25 to 50 °C, total auxiliary power increases around six times, energy consumption increases by 35 % per kilometer, and mean COP drops by 39 % for the US06 driving cycle. This model is applied to various Indian cities to compare energy consumption. Drivetrain model parameters like vehicle mass, motor and transmission efficiency, and road gradability are varied to estimate their effect on battery electric vehicle energy consumption. Considerable effects of solar load, cabin's initial temperature, and cabin's target temperature are observed. Two different cooling loops for the battery thermal management are simulated to observe terminal voltage and internal cell temperature response. A temperature drop of 5 °C in internal cell temperature is observed when cabin exit air is blown on the battery radiator instead of ambient air. The effect of road gradability and coolant flow rate on power electronics transistor and diode temperature are also quantified.

Thermal conductive polymer composite with similar PTC effect through latent foaming

At present, heat dissipation and heat insulation in power battery packs are two very important aspects in thermal management of electric vehicles. Heat dissipation is needed when the battery is working normally, but heat insulation is needed when the battery is thermal runaway. Now one surrounding material cannot meet these two opposite requirements at the same time. In this work, foaming agent as an initiator was used to prepare a thermal conductive polymer composite. Its thermal conductivity decreases sharply when the temperature rises to 160–180 °C, which shows a similar Positive Temperature Coefficient (PTC) effect. The main factors that affect its thermal conductivity, including foaming agent content, filler type, filler particle size and recombination are also discussed. By controlling the ratio of recombination, the change rate of thermal conductive PTC composite with latent foam structure can increase from only 4 times of formulation with only BN filler to 11 times of formulation with 80%Al2O3/20%BN below 190 °C. The infrared thermal imaging test further confirms that the prepared samples have good thermal conductivity at normal temperature, and the thermal conductivity decreases rapidly with the increase of temperature, confirming the effect of latent foam structure.

An optimal thermal management system heating control strategy for electric vehicles under low-temperature fast charging conditions

• An improving fast charging protocol is proposed to avoid lithium plating. • A multi-stage heating control strategy based on the battery temperature is developed. • Dual crucial objectives, heating energy consumption and charging time are balanced. • An optimal heating control strategy for low-temperature fast charging is proposed. • The optimal control strategy can reduce heating energy consumption by 11.61%. Electric vehicle thermal management system (EVTMS) and its corresponding control strategy are essential to ensure the battery performance at low temperatures. Due to the complexity of the low-temperature fast charging process, it is necessary to comprehensively consider the battery heating and charging performance when developing the heating strategy. However, most studies only focus on the charging time. In this context, an EVTMS is investigated in this paper, and the simulation models are established. In addition, the battery heating and charging performance under low-temperature fast charging conditions are analyzed by experiment and simulation. An improved fast charging protocol for reducing the battery-lifetime degradation is proposed. Moreover, an EVTMS multi-stage heating control strategy is developed to realize the cooperative control with the improved charging strategy. Taking dual crucial yet conflicting factors, heating energy consumption and charging time, as the optimization objectives, the proposed EVTMS control strategy is optimized using genetic algorithm. And an optimal heating control strategy is obtained. The results show that compared with the strategy only considering the charging time, the optimal strategy can reduce the heating energy consumption by 11.61% and increase the charging efficiency by 1.2%, only with the increase of the charging time by 2.98 min.