Management System For Electric Vehicles Research Articles

Design of an Intelligent Energy Management System for Electric Vehicle Charging Station

In today’s world there are more outcomes in environmental change due to the overutilization of petroleum products in this manner prompting a genuine effect on the climate. So there is a need for a substitute answer for lessen the consumption of such non – sustainable assets. One such exertion made in the field of Freeways is the advancement of "Solar Freeways" which can be an elective arrangement. Sun oriented streets consolidate various arrangements in one – it can assist us with improving the creation of power utilizing sun based boards, to give a computerized stage to our future country's ventures like Smart Cities, and to work with the arising electric vehicles that supplant the petroleum driven vehicles and substantially more. Motivated by the fact that there are numerous amount of clean and sustainable energy we receive from roadways, the following study puts forward some of the event and application of an innovative charging method for the renewable energy driven electric cars, buses by using the roadway and also implementation of revolutionary nanotechnology along with the latest best in the house power electronics and power system analysis tools. A small scale prototype model was made by our team to attest the working of smart inductive charging process. Our project team was successful to improve the working of the model by improving the use of the preinstalled solar panels and also implement its use on the very concept we are trying to improve. On the vehicle, there will be the use of coils which are experimentally made for the flow of charges that are needed to provide charge to a moving electric vehicle (EV). The detailed strategy is presented in this report. Key Words: Environmental change, Overutilization of petroleum products, Solar Freeways, Renewable energy, Electric vehicles (EVs), Smart Cities, Nanotechnology

A novel hybrid liquid-cooled battery thermal management system for electric vehicles in highway fuel-economy condition

A hybrid liquid cooling system that contains both direct and indirect liquid cooling methods is numerically investigated to enhance the thermal efficiency of a 21700-format lithium-ion battery pack during the discharge operation. One of the most significant challenges that liquid-based direct cooling systems face is the filling of the heat capacity of the coolant during the cooling process, hindering the effective dissipation of heat generated from batteries. This paper aims to introduce a battery thermal management system to address this issue. In the present study, the influences of immersion and flow cooling methods using HFE-7100 and water (as working fluids), inflow velocities of cooling channel and tubes, parallel and counter flow, battery cell space, and highway fuel-economy test on the temperature distribution of batteries were studied comprehensively. Results highlight that immersion cooling with water outperforms due to the lower thermal conductivity of HFE-7100. In addition, Flow cooling significantly reduces the battery pack's highest temperature and non-uniformity compared to immersion. According to the numerical results, using cooling tubes as an indirect cooling system integrated with the direct flow cooling method can remarkably improve the thermal efficiency of the battery pack. Moreover, results exhibited that counterflow between cooling tubes/channels can keep the highest temperature and temperature variance of Li-ion battery package below 32.15 °C and 3.04 °C, respectively. Varying battery cell spaces shows that a 14 mm space reduces the battery package's highest temperature by 1.54 °C compared to a 10 mm space. Finally, highway fuel-economy condition is applied to the simulations of this study, illustrating the effect of an innovative hybrid battery thermal management system for a 21700-type Li-ion battery pack.

Experimental investigation on the flow boiling of R134a in a plate heat exchanger with mini-wavy corrugations

As a common component in various applications, the two-phase heat transfer of plate heat exchanger has been frequently studied. However, further investigations are still required on the flow pattern, especially for those with new plate structure brought with the emergence of new applications. This study presented an experimental investigation on the flow boiling of R134a in a plate heat exchanger with mini-wavy corrugations designed for thermal management system of electric vehicle (EV). The flow pattern transitions in the test section were captured and discussed, meanwhile the effects of vapor quality and mass flux on the variation of heat transfer coefficient (HTC) were analyzed. Based on the observation, the two-phase flow pattern developed from pulsating film flow, then rough stream flow and finally to thin stream flow with the increase of vapor quality. The flow pattern map was determined with the superficial momentum of the liquid and vapor phase refrigerant, while the empirical correlations were developed based on two-phase Weber number to predict the transitions between the flow patterns. The HTC showed an intermediate increase firstly under low vapor qualities, and rapidly decreased after reaching the peak value at the vapor quality of 0.45-0.6. In addition, the experimental data were compared with the present correlations, and a new Nu correlation was developed considering the transitions of flow patterns, showing an optimal prediction on the experimental data with the mean absolute error of 11.3%.

Battery Thermal Management System for Electric Vehicle (EV)/Hybrid EV (HEV) with the Incorporation of POA-FSO Strategy

A hybrid technique is proposed for electric vehicles (EVs) or hybrid electric vehicles (HEVs) with a battery thermal management system (BTMS). The proposed hybrid method is the combined execution of the Pelican Optimization Algorithm (POA) and Firebug Swarm Optimization (FSO). The hunting behavior of pelicans is improved with the help of the FSO technique; hence, it is named the POA-FSO strategy. Here, a battery of 36 lithium-ion (Li-ion) cells is considered. The proposed method of analyzing battery thermal performance analyzed factors like heat flux from the battery cell to the passage spacing size, cooling air and the cooling air’s mass flow rate (MFR). The BTMS performance is studied under maximum battery unit temperature, pressure drop and temperature uniformity. The proposed method enhances the coolant passage spacing and decreases the temperature difference in the battery cells. The proposed approach is executed on the MATLAB platform, and its performance is compared with existing approaches. From the results, it is concluded that the MFR maximizes, and a nonuniform distribution of the MFR of the passage occurs. By using the proposed approach, the maximal temperature change of cooling air among the passages is 2.0[Formula: see text]K, the maximal temperature change between the battery cells is 7.5[Formula: see text]K and a pressure drop of 228.03[Formula: see text]Pa is obtained.

Design and Analysis of Battery Management System for Electric Vehicles

Abstract: This article presents a design for both the hardware and software components of the BMS, enabling battery monitoring and management. The Battery Management System (BMS) is a fundamental component of electric vehicles, primarily utilized to ensure battery safety and enhance battery lifespan. The hardware component encompasses the design of voltage acquisition circuitry, second-order filtering circuitry, sampling and holding circuitry, CAN bus communication circuitry, and other relevant features. The software section comprises subroutines for battery information collection, equalization circuitry, SOC estimation, and other relevant features. The BMS developed in this study successfully collects voltage, temperature, current, and other relevant information, and accurately estimates SOC and other crucial parameters. Testing confirmed that the battery management system precisely collects battery voltage, current, and temperature information, while the SOC estimation achieves a relatively high degree of accuracy.

Decoupling control of an integrated direct cooling thermal management system for electric vehicles

As the requirement for Li-ion battery thermal management system (TMS) in electric vehicles (EVs) rises, an integrated direct cooling thermal management system with high compactness and energy efficiency has been developed. The integrated system is based on a vapor-compression refrigeration cycle, forming a dual-evaporator system, and adopts a direct cooling scheme on the battery side, which brings high coupling effects. A novel decoupling control strategy was proposed and a weight-based fuzzy logic control algorithm was applied to implement the strategy, achieving effective temperature control and reasonable refrigerant distribution between the battery side and cabin side. Experiments conducted under various scenarios demonstrated that the average temperature of both the battery pack and cabin could be stably controlled around different target values. Maximum fluctuations were effectively limited to less than 0.7 °C in different scenarios. The implementation of this decoupling control strategy has opened up new possibilities for the application of direct cooling TMS in multi-target systems.

Battery/Supercapacitor Energy Management system for Electric Vehicle

Electric vehicles (EVs) require appropriate design and sizing of their energy sources and proper management. The solution will be an energy efficient with cost-effective, increased lifespan, and an increase in the vehicle’s range. As per theory of evolution the model and rating calculations are discussed. Also this paper addresses the distribution of power within two energy sources, adopting a converter. Only one energy element unable to meet each preferred parameters. In addition to assisting electric vehicles in acceleration, the Hybrid Energy Storage System captures regenerative braking energy. By controlling the current of battery as consistent as viable at the time of picks, power management is primarily concerned with reducing battery stress and merging supercapacitors to supply instantaneous current at the time of pick and to recover power during deceleration. According to the results of HESS and experimental setup, current of battery is controlled as consistent as at the time of acceleration when the power management algorithm is implemented. In other words, only normal current is provided by the battery at the time of picks, while transitory current is provided via the ultracapacitor during acceleration.

Experimental study on an integrated thermal management system for electric vehicle with collaborative control

The fast growth of power battery energy density and driving conditions increasingly complex and extensive brings significant challenges to electric vehicles' integrated thermal management system. This study investigates cooperative control strategies for battery cooling refrigerant-based and AC cooling system to enhance efficiency and achieve integrated thermal management. The results demonstrated the efficacy of Com-VOVs mode, which enables the active distribution of cooling capacity across both circuits. It proves the method proposed have benefits over single-factor compressor regulation. Furthermore, compared to the threshold control mode, the Com-VOVs method improved the COP performance of the system significantly. It can efficiently lower pressure drop loss maximum 52.24% of the cold plate and stabilize the air temperature at the AC outlet. This work shows the benefits and importance of compressor and VOVs regulating collaboration for the integrated thermal management system through experiments.

Designing a battery Management system for electric vehicles: A congregated approach

In many high-power applications, such as Electric Vehicles (EVs) and Hybrid Electric Vehicles (HEVs), Battery Management System (BMS) is needed to ensure battery safety and power delivery. BMS performs cell balancing (CB), State of Charge (SoC) estimation, monitoring, State of Health (SOH) estimation, and protective operation. To safeguard and optimize battery performance, required essential functionalities must be enabled. To optimize battery system performance, safety, and longevity, including temperature management, cell balancing, and communication protocols. This article provides an architecture that includes both a hardware demonstration and a simulation of the continuous on-time control approach for systematic measurement of Voltage, current, and temperature in EVs. A single-ended primary-inductance converter (SEPIC) DC-DC converter, Analogue Front End (AFE), and balancing circuits provide the optimal supply for proposed congregated BMS process. The effectiveness of proposed congregated design performance is validated through meter and sensor measurements for voltmeter, current, and temperature. The numerical error between proposed BMS and conventional measurements is relatively low for voltage (0.09 V), current (0.05 A), and temperature (0.09 °C). In the end, the simulated results and hardware results are benchmarked that the proposed congregated BMS design can regulate temperature, prevent overcharging and over-discharging, and balance the battery cells inside a given battery module.

Performance analysis of CO2 thermal management system for electric vehicles in winter

CO2 is well-suited for thermal management systems (TMSs) in electric vehicles, particularly in winter when both the cabin air and the battery require heating. However, due to the distinct heat exchange boundary conditions of these two heated components, traditional theories of optimal operation of CO2 cycle are not applicable. In this paper, the system characteristics of a CO2 TMS in the cabin-and-battery mixed heating mode are comprehensively investigated. The results show that there is a pseudo-optimal discharge pressure that maximizes the COPTMS, regardless of whether the system is operating in a transcritical or subcritical mode. In addition, besides the global optimal COPTMS, there may still be other local maximum points, which are determined by the CO2 flow distribution in both gas coolers and the COP rise rate of the battery cycle. Furthermore, this work offers a thorough investigation of the impact of essential factors on the pseudo-optimal discharge pressure and proposes an accurate prediction approach for the best control of the CO2 TMS. The CO2 TMS can still ensure a COPTMS above 2.0 to meet the thermal demands of both the cabin and the battery even under the challenging operating circumstances of −20 °C, proving the technology's great competitiveness.

Pulse charging based intelligent battery management system for electric vehicle

Electric vehicles (EVs) are now an important part of the automotive industry for two main reasons: decreased reliance on oil and reduced air pollution, which helps us contribute to the development of an environmentally friendly environment. EV buyers examine overall vehicle mileage, recharge time, vehicle mileage after every charge, batteries charging/discharging security, lifespan, charged rate, capability, and temperature increase. A new improved pulse charging technique is proposed, in which the battery is charged using proportional integral derivative (PID) control action and a neural network. A PID controller is used to develop the charging unit in this design. The feed forward neural network was used to determine the values of the PID control parameters. The battery management system (BMS) ensures that this designed battery charging system takes less time to charge the battery efficiently. The system is built with MATLAB/Simulink.

Pulse charging based intelligent battery management system for electric vehicle

Electric vehicles (EVs) are now an important part of the automotive industry for two main reasons: decreased reliance on oil and reduced air pollution, which helps us contribute to the development of an environmentally friendly environment. EV buyers examine overall vehicle mileage, recharge time, vehicle mileage after every charge, batteries charging/discharging security, lifespan, charged rate, capability, and temperature increase. A new improved pulse charging technique is proposed, in which the battery is charged using proportional integral derivative (PID) control action and a neural network. A PID controller is used to develop the charging unit in this design. The feed forward neural network was used to determine the values of the PID control parameters. The battery management system (BMS) ensures that this designed battery charging system takes less time to charge the battery efficiently. The system is built with MATLAB/Simulink.

An intelligent converter and controller for electric vehicle drives utilizing grid and stand-alone solar photovoltaic power generation systems

In this study, a battery energy management system for electric vehicle (EV) applications is proposed with a standalone photovoltaic (PV) source and controlled based on the availability of grid, PV source, load consumption, and energy stored in the battery. This paper proposes a single-ended primary-inductance converter (SEPIC) DC-DC converter for charging the battery through the utility and PV source that provides good load regulation. The bidirectional nature of the proposed DC-DC converter provides the charging and discharging of the EV battery in the succeeding modes of operation, i) grid-tied charging, ii) PV-tied charging, iii) discharging to the load in the absence of utility and PV source, and iv) regenerative braking. An improved perturb and observe-based maximum power point tracking (MPPT) algorithm is proposed to track the maximum power from the PV source. In addition, to handle the four modes of operation, a dedicated controller is also proposed. Firstly, the proposed system is validated using MATLAB/Simulink software by considering different operating conditions, and the performance is compared with the traditional MPPT algorithms. Finally, the effectiveness of the suggested system is validated through an experimental prototype. The result proved the superiority of the converter and controller over the traditional systems.<div align="center"> </div>

Numerical Analysis of Battery Thermal Management System of Electric Vehicle

This study is modelling the direct liquid cooling system of battery used in Electric Vehicle. The purpose of the study is to investigate the performance of the Li-ion battery model under different input of parameters and to evaluate the optimum parameters for the battery thermal management system model to maintain at its peak performance. SolidWorks and ANSYS are used to model and simulate the battery whereas MINITAB software is selected for conducting the statistical analysis. Heat flux, mass flow rate at the inlet and the thickness of the battery model has been selected as input of the simulation. The obtained results show that the heat transfer coefficient is increasing with the higher heat flux and mass flowrate but decreasing with the thickness of the battery model. Pressure drop remains constant when heat flux varies but increasing with mass flow rate and inversely proportional with the thickness of battery. For statistical analysis, an optimum value for the parameters is proposed to maintain the battery to operate with a highest heat transfer coefficient but lowest in pressure difference. Overall, the study has been conducted successfully and fulfilled the objectives stated.

Development and Application of an Energy Management System for Electric Vehicles Integrated with Multi-input DC-DC Bidirectional Buck-Boost Converter

The rise in environmental pollution, demand for fossil fuels, and higher fuel economy vehicles has raised concerns about the creation of new and efficient transportation vehicles in recent days. These days, most developments in electric vehicles concentrate on making the vehicles more pleasant to ride in. Nonetheless, the emphasis now should be on energy and its most efficient use. To do this, you must give your attention to the origin of the automobile. The answer to this problem may be found in hybrid energy storage systems (HESS). This work is concerned with the design and implementation of an effective energy management system in electric vehicles (EVs) equipped with an active HESS consisting of a battery and a super capacitor via the incorporation of load sharing into this hybridization under a variety of load demand scenarios. To address the demands of high fuel efficiency vehicles, automotive firms are focusing on the development of diesel-engine operated vehicles, electric vehicles, fuel-cell vehicles, plug-in electric vehicles, and hybrid electric vehicles. A Multi-input Bidirectional Buck-Boost (MIB3) DC-DC converter is proposed in this dissertation to provide a greater conversion ratio to the input DC voltage. The multi-input converter recommended has fewer components and a simpler control method, making it more trustworthy and cost-effective. This converter also has bidirectional power flow functionality, making it suitable for charging the battery during regenerative braking in an electric or hybrid vehicle. Three different energy sources are used in the suggested topology: a photovoltaic (PV) panel, a battery, and an ultra-capacitor

Accurate and Efficient Energy Management System of Fuel Cell/Battery/Supercapacitor/AC and DC Generators Hybrid Electric Vehicles

The development of hybrid electric vehicles (HEVs) is rapidly gaining traction as a viable solution for reducing carbon emissions and improving fuel efficiency. One type of HEV that is gaining significant interest is the fuel cell/battery/supercapacitor HEV (FC/Bat/SC HEV), which combines fuel cell, battery, supercapacitor, AC, and DC generators. These FC/B/SC HEVs are particularly appealing because they excel at efficiently managing energy and cater to a wide range of driving requirements. This study presents a novel approach for exploiting the kinetic energy of a sensorless HEV. The vehicle has a primary fuel cell resource, a supercapacitor, and lithium-ion battery energy storage banks, where each source is connected to a special converter. The obtained hybrid system allows the vehicle to enhance autonomy, support the fuel cell during low production moments, and improve transient and steady-state load requirements. The exploitation of kinetic energy is performed by the DC and AC generators that are linked to the electric vehicle front wheels to transfer the HEV’s wheel rotation into power, contributing to the overall power balance of the vehicle. The energy management system for electric vehicles determines the FC setpoint power through the classical state machine method. At the same time, a robust speed controller-based artificial intelligence algorithm reduces power losses and enhances the supply efficiency for the vehicle. Furthermore, we evaluate the performance of a robust controller with a speed estimator, specifically using the adaptive neuro-fuzzy inference system (ANFIS) and the model reference adaptive system (MRAS) estimator in conjunction with the direct torque control-support vector machine (DTC-SVM), to enhance the torque and speed performance of HEVs. The results demonstrate the feasibility and reliability of the vehicle while utilizing the additional DC and AC generators to extract free kinetic energy, both of which contributed to 28% and 24% of the total power for the vehicle, respectively. This approach leads to a vehicle supply efficiency exceeding 96%, reducing the burden on fuel cells and batteries and resulting in a significant reduction in fuel consumption, which is estimated to range from 25% to 35%.

Experimental and numerical simulation study on the integrated thermal management system for electric vehicles

Battery thermal management technology can realize the orderly management of heat, which is an important way to improve the safety and lifespan of batteries in electric vehicles (EVs). Herein, we propose an integrated battery thermal management system (IBTMs) that it includes both heat dissipation and low-temperature heating function. In the integrated structure design, the composite phase change materials (CPCM) have a strongly heat absorbed capability due to the large latent heat, and the thin polyimide heating film (PHF) can conveniently assemble into the battery module. The experiment and simulation results verified that the electrochemical performance of battery module can be achieved an excellent recoverable when employed a heating strategy of continuous pulse warm-up combined with battery at low-power self-preheating. Compared with the normal temperature of 10 °C, the capacity of battery module of charge and discharge is recovered to 92.1 % and 93.3 %, respectively. Besides, the heat dissipation performance tests result also show that the IBTMs has an excellent temperature control and uniform capability. The maximum temperature and maximum temperature difference of battery module is always controlled within 52 °C and 1.8 °C respectively, even if the battery module is continuously cycled 5 times with 2C-1C test protocol at extremely high temperature of 40 °C.

Energy Storage Charging Pile Management Based on Internet of Things Technology for Electric Vehicles

The traditional charging pile management system usually only focuses on the basic charging function, which has problems such as single system function, poor user experience, and inconvenient management. In this paper, the battery energy storage technology is applied to the traditional EV (electric vehicle) charging piles to build a new EV charging pile with integrated charging, discharging, and storage; Multisim software is used to build an EV charging model in order to simulate the charge control guidance module. On this basis, combined with the research of new technologies such as the Internet of Things, cloud computing, embedded systems, mobile Internet, and big data, new design and construction methods of the energy storage charging pile management system for EV are explored. Moreover, K-Means clustering analysis method is used to analyze the charging habit. The functions such as energy storage, user management, equipment management, transaction management, and big data analysis can be implemented in this system. The simulation results of this paper show that: (1) Enough output power can be provided to meet the design and use requirements of the energy-storage charging pile; (2) the control guidance circuit can meet the requirements of the charging pile; (3) during the switching process of charging pile connection state, the voltage state changes smoothly. It can provide a new method and technical path for the design of electric vehicle charging pile management system, which can effectively reduce the system’s operation and maintenance costs and provide more friendly and convenient charging services.

A refrigerant-injection heat pump-based efficient integrated thermal management system for electric vehicles approaching the wide temperature range in China

The integrated thermal management system of electric vehicles is responsible for the temperature regulation of the cabin and electrical system. The wide temperature range of vehicles specifies the operating conditions required for different regions, which is −33 – 39 °C in China. Through experimental studies conducted on heat pump systems and thermal analyses of electrical systems, this study innovatively developed an efficient integrated thermal management system based on a refrigerant-injection heat pump. In addition, a simulation platform for the system was established using the advanced modeling environment for performing simulation of engineering systems (AMESim) software to evaluate the system performance. The results showed that the stability and efficiency of battery cooling based on the intermediate heat exchanger were better than those obtained with a dual evaporator setup. The proposed solution could reduce energy consumption by 30% at an ambient temperature of 35 ℃. The thermal management system with the heat recovery for the motor and electric control at high temperatures could reduce the energy consumption by 11.98% – 56.69% and meet the heating condition of −22.04 ℃. The integrated thermal management system based on a refrigerant injection heat pump widened the operating range during the highway fuel economy test (EPA-420-B-12-001). Aided by electric heating, the simulation system developed in this study could satisfy the load requirements for the wide temperature range in China.

Koopman Model Predictive Control of an Integrated Thermal Management System for Electric Vehicles

AbstractThis paper is concerned with energy efficient operation of an integral thermal management system (ITMS) for electric vehicles using a nonlinear model predictive control (MPC). Driven by a heat pump (HP), this ITMS can handle battery thermal management (BTM) while serving the need for cabin cooling or heating need. The objectives of the ITMS MPC control strategy include minimization of power consumption and achieving temperature setpoint regulation for the battery and cabin space based on predictive information of traction power and cabin thermal load. The control design is facilitated by a gray-box modeling framework, in which the nonlinear dynamics of HP subsystem are characterized with a data-driven Koopman subspace model, while the BTM subsystem dynamic is a bilinear physics-based model. The computational efficiency of the proposed MPC framework is improved with two aspects of convexification for the underlying receding-horizon constrained optimization problem: the Koopman-operator lifting and the McCormick envelopes implemented for handling the bilinear dynamics. The proposed control method is evaluated with simulation study, by developing a Modelica-Python cosimulation platform via the functional mockup interface (FMI), where the electric vehicle (EV)-ITMS plant is modeled in Modelica with Dymola and the MPC design is implemented in Python. By benchmarking against a recurrent-neural-networks (RNN) model based nonlinear MPC, the simulation results validate the effectiveness and improved computational efficiency of the proposed method.