Design Of Electric Vehicle Research Articles

Closed-Loop Control and Plant Co-Design of a Hybrid Electric Unmanned Air Vehicle

Abstract Novel conceptual aircraft designs have been enabled by more electrified aircraft components providing enhanced capability and versatility. Through the advancement of multidisciplinary design optimization, control co-design methods have become a popular approach for system design conceptualization wherein the plant and control actions are designed simultaneously to account for the coupling between vehicle subsystems and power management systems. Many prior efforts have focused on open-loop control co-design that can later be adapted for a more realistic operating case. This work focuses on the development and scalability of closed-loop control co-design that would result in a physically realizable plant and closed-loop control law. The theoretical approach is demonstrated practically through the design of a hybrid electric unmanned air vehicle and two feedback controllers that operate the hybrid power split and propulsion system. The system is designed to complete a dynamic seven phase mission consisting of multiple cruise, dash, engage, dive, and climb segments as quickly as possible. Given the scale of the dynamic design problem, a convergence study is introduced that facilitates accurate and computationally tractable design optimization studies. The study is conducted for independent, sequential, and simultaneous design approaches. The results indicate high-speed motors, high voltage batteries, and responsive control gains result in a fast vehicle with high thrust-to-weight ratio. The simultaneous design solution had the best closed-loop performance, outclassing a baseline system design by over 30%.

The prospect of chassis structure design for new energy battery electric vehicles

More focus has been placed on creating new energy cars that are safer and more energy-efficient due to the development of new energy vehicle technologies and their strategic importance in addressing current energy and environmental issues. The chassis system's primary components, whether for a conventional fuel vehicle or a new energy vehicle, are the braking, suspension, and steering subsystems. The functioning, comfort, and safety of modern energy vehicles are strongly correlated to their structural design. At the moment, the design of new energy vehicle chassis is mostly based on refining and adapting the chassis of conventional fuel vehicles. However, new energy vehicles have distinct driving systems compared to conventional vehicles. Thus it is important to account for these variations in the layout and make it compatible with the whole system. The chassis structural design of new energy cars is more adaptable and affects vehicle performance compared to fuel-powered vehicles. The integrated battery and high amount of unsprung mass affect the center of gravity and stability of the new energy vehicle. The coordination and collaboration between the power battery module and the chassis construction must therefore be carefully considered, as well as their effects on the entire vehicle performance, including its safety and economic effectiveness. In conclusion, thoroughly examining the chassis structure design plan for new energy vehicles is crucial for advancing these vehicles.

PerfECT Design Tool: Electric Vehicle Modelling and Experimental Validation

This article addresses a common issue in the design of battery electric vehicles (BEVs) by introducing a comprehensive methodology for the modeling and simulation of BEVs, referred to as the “PerfECT Design Tool”. The primary objective of this study is to provide engineers and researchers with a robust and streamlined approach for the early stages of electric vehicle (EV) design, offering valuable insights into the performance, energy consumption, current flow, and thermal behavior of these advanced automotive systems. Recognizing the complex nature of contemporary EVs, the study highlights the need for efficient design tools that facilitate decision-making during the conceptual phases of development. The PerfECT Design Tool is presented as a multi-level framework, divided into four logically sequential modules: Performance, Energy, Currents, and Temperature. These modules are underpinned by sound theoretical foundations and are implemented using a combination of MATLAB/Simulink and the vehicle dynamics software VI-CRT. The research culminates in the validation of the model through a series of experimental maneuvers conducted with a Tesla Model 3, establishing its accuracy in representing the mechanical, electrical, and thermal behavior of BEVs. The study’s main findings underscore the viability of the design tool as an asset in the initial phases of BEV design. Beyond its primary application, the tool holds promise for broader utilization, including the development of active control systems, advanced driver assistance systems (ADAS), and solutions for autonomous driving within the domain of electric vehicles.

Vibration and noise analysis of a vehicle equipped with magneto rheological damper

Magneto rheological fluid, often known as MR fluid or MRF, is a type of smart fluid whose properties can be altered upon the application of magnetic field. Using an applied magnetic field, these fluids can transmit force in a controlled way. Due to its beneficial characteristics, such as low power consumption, force controllability, and quick reaction, it leads to its various possible control-based applications in the automobile sector, such as suspensions, brakes, fluid clutches, etc. In this study, applicability of MR dampers to suppress vibration and noise of an electric vehicle is evaluated using the phenomenological models such as Bingham and Bouc-Wen. These models are integrated into the suspension system of a quarter-car model and its performance is studied using numerical methods. These models involve non-smooth, nonlinear differential equations that can be solved using numerical methods. Model based suspension control systems may be developed for better ride comfort using this approach. The potential of this approach for design of electric vehicles is explored.

East and West: global technological confrontation

In recent years the technological rivalry between China and the USA has become increasingly intense as both countries compete for dominance in the following promising technological areas: in the creation of artificial intelligence systems, in the production of equipment for 5G generation communication networks, in quantum computing, in the design and manufacture of electric vehicles and in biotechnology research. As China’s economy grows and its technological capabilities expand, the USA is increasingly concerned about the consequences of China’s rapid technological growth for national security, economic competitiveness and for global dominance of the USA. In response to China’s technological rise, the USA has taken a number of steps to restrict China’s access to “sensitive” technologies and protect its own interests. The result of such actions was a complex and dynamic confrontation that has an impact on the future of the global economy and technological innovation. This article examines a retrospective of the relationship between the two most developed economies of the world; studies the factors that led to the digital confrontation; analyzes the potential impact of digital competition on the global economy and also considers the prospects for further development of China and the USA as technological giants of modernity.

Double Coupling In-Wheel IPT System for Electric Vehicles

The electric automotive industry revolutionizes the transportation sector with new disruptive technologies like wireless charging systems and the tire industry is no exception. New airless and sustainable tire designs offer new possibilities to embody wireless charging technologies. This paper presents a novel in-Wheel Inductive Power Transfer (inWIPT) batteries charger design for electric vehicles (EV). The proposed system uses two magnetic couplers (MC) to transfer the energy: one from the off-board side to the wheel and another from the wheel to the on-board side. The proposed configuration keeps the air gap between the off-board transmitter pad and the wheel receiver to a minimum and almost independent of the vehicle type (Sedan, Suv, Truck). The two MCs are connected by a new resonant tank which modifies the voltage transfer characteristics. A step by step methodology that identifies the operational range of the mutual inductances, based on certain design specifications and constraints, is also presented. Experimental results validate the proposed inWIPT in a quasi load independent voltage operation in different coupling charging scenarios and a maximum output power of 2.6 kW with an efficiency of 89.3 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\%$</tex-math></inline-formula> .

Design of Active Disturbance Rejection Controller for Trajectory-Following of Autonomous Ground Electric Vehicles

In this paper, the concept of symmetry is utilized in the promising trajectory-following control design of autonomous ground electric vehicles—that is, the construction and the solution of active disturbance rejection controllers are symmetrical. This paper presents an active disturbance rejection controller (ADRC) for improving the trajectory-following performance of autonomous ground electric vehicles (AGEV) with an advanced active front steering system. Since AGEV trajectory dynamics are inherently affected by complex traffic conditions, various driving maneuvers, and other road environment, the main control objective is to deal with the AGEV trajectory control challenges of system uncertainties, system nonlinearities, and external disturbance. First, the vehicle dynamics trajectory-following model and its state space representation system are established. Then, the augmented control-oriented vehicle-trajectory-following system with dynamic error is developed. The resulting active disturbance rejection controller of the vehicle-trajectory-following system is finally designed using the trajectory performance index and active disturbance compensation, and the stability of the active disturbance rejection controller is also analyzed and derived via Lyapunov stability theory. The effectiveness of the proposed controller is validated through double lane change and serpentine maneuvers under the co-simulation platform of MATLAB/Simulink-Carsim®. Simulation results show that the designed controller provides enhanced vehicle-trajectory-following performance compared to the linear quadratic regulator controller (LQR) and model predictive controller (MPC). It will provide a certain guidance for the controller engineering design of the AGEV trajectory-following system.

Modeling, Model Calibration, and Characterization of Graphite Anodes from Coal Derived Carbon

Most current production electric vehicles (EVs) contain cells with a battery pack or module in order to maintain electrical conductivity, prevent fatigue due to vibrations, and provide efficient cooling. Various module hardware has to be designed in order to facilitate the efficient rejection of heat and contain volume change due to operation and battery cell aging. As we see a shift towards EVs both globally and domestically, the time from concept development to vehicle production needs to rapidly increase. The use of model-based engineering is critical to driving rapid design and virtual prototyping of electric vehicles to ensure that battery module components meet EV requirements.Currently, empirical data is used to characterize and parameterize battery models that are used to drive design decisions at the battery cell and battery module level. Typical vehicle level use profiles such as the Hybrid Pulse Power Characterization (HPPC) profile, constant rate discharging, constant rate charging, and US06 drive cycles are traditionally used to parameterize battery models. In this work, we discuss select cell level testing profiles, evaluate the electrochemical transport and reaction parameters that are estimated using a porous electrode model, and provide insight and recommendations based on data from coal derived graphite for battery applications.

Finite element modeling of electric vehicle power battery pack and its influence analysis and test research at body-in-white stage

Compared with the design of traditional fuel vehicles, the design of electric vehicles has its uniqueness, consisting mainly in that the body design must be able to adapt to the new power system and its layout. Power battery pack is an important factor affecting the body design of electric vehicles. In order to study the modeling of power battery packs and its impact on body performance, it was proposed to use the finite element method for modeling the power battery pack and analyzing its influence on the performance of the body-in-white. Based on a certain electric vehicle, the basic body-in-white model and the body-in-white model with the mass point addition and the refined model of the power battery pack were established, the static stiffness of the body-in-white simulation results of different models were compared and analyzed, and finally the effectiveness of the simulation model was verified through bench tests. Based on this effective model, the influence of the power battery pack on the modal and strength of the body-in-white was analyzed. The results show that the established refined model of the power battery pack has higher computational accuracy. Besides, the power battery pack can significantly increase the static stiffness of the electric vehicle body-in-white, effectively optimize the first-order torsion frequency and the first-order front cabin yaw frequency of the body-in-white, reduce the first-order bending frequency of the body-in-white, and greatly increase the risk of static strength failure of the body-in-white. In the setting of body performance goals and structural development, the influence of the power battery pack cannot be ignored.

A flexible optimization study on air-cooled battery thermal management system by considering of system volume and cooling performance

When the battery temperature exceeds the normal range, the battery efficiency performance, and life will be significantly reduced, and the battery may even explode. Therefore, an optimal battery thermal management system is required to dissipate heat efficiently. The existing research focuses on the structural design to reduce the maximum temperature of the system. However, the volume of the cooling system is also important for electric vehicle design, which has received little attention. In this study, a new flexible optimization strategy for a battery thermal management system is proposed, which is a hybrid of system volume and cooling performance and can determine the appropriate optimized structure according to the engineering applications. The proposed method belongs to four steps: optimization system design, establishment of shortcut computation codes, multi-objective optimization and comprehensive fuzzy decision making. The numerical simulation based on computational fluid dynamics (CFD) is used to verify the cooling performance of the optimized system. Compared with the three existing designs of battery thermal management system from previous literatures, the volume is reduced by a maximum of 13.01 %. In the process of stable heat generation, the maximum temperature difference decreased by 65.79 %, 40.65 %, and 63.69 %, and the temperature uniformity increased by 65.87 %, 34.93 %, and 60.80 %, respectively. In the unsteady heat generation of the battery pack, at the discharge rate of 5C, the maximum temperature difference decreases by 2.28 K, and the maximum temperature difference and temperature uniformity decrease by 57.11 % and 49.15 %, respectively.

Continuous Operation of a Half-Bridge with Multi-Parallel GaN Power Devices for Increased Current Capability

GaN power devices improve the performance in power conversion circuits. Since the current rating of the GaN devices is still small, many devices must be connected in parallel to create a large-current power module. Device cooling and low stray inductance are the major challenges in designing a high-power half-bridge circuit with multi-parallel GaN devices. In order to overcome these challenges, we propose an inverter circuit structure with 12 parallel GaN devices capable of double-sided cooling and a well-balanced stray inductance. Such a system is applicable to electric vehicle design.

Design and Performance Analysis of Hybrid Electric Vehicles using Matlab/Simulink

In this paper introduces an integrated method for the design and performance analysis of hybrid electric vehicles. This method considers a set of parameters that influence the system's performance. This project presents an approach for modelling electric vehicles considering the vehicle dynamics, drive train, rotational wheel and load dynamics. The performance of the hybrid electric vehicle is not satisfactory owing to the difficulties of optimal gain selections. To overcome this problem, a new fuzzy logic controller is required to set the rules for better performance. Therefore, in this project fuzzy logic-based gain tuning method for PID controller is proposed and compared with some previous control techniques for the better performance of electric vehicles with an optimal balance of acceleration, speed, travelling range, improved controller quality and response. The model was developed in MATLAB/Simulink, simulations were conducted, and results were observed

Design of a sustainable electric vehicle sharing business model in the Brazilian context

Design of a sustainable electric vehicle sharing business model in the Brazilian context

A DETAILED REVIEW ON ENGINEERING DESIGN OF ELECTRIC VEHICLES

A potential system to resolve the issue of environmental change is to energize the transport system. The market's acknowledgment of electric vehicles fundamentally affects various regions which includes the power network. A few guidelines have been established to hurry the organization of electric vehicles, and the vertical pattern in reception of electric vehicles as of late has been empowering. The innovation for the electric vehicle's parts have kept on propelling, making them all the more broadly taken on. Despite the monetary and ecological advantages, charging electric vehicles impacts how the flow network capabilities. To resolve this issue, suitable charging the board measures can be set up. Likewise, the reconciliation of electric vehicles into the brilliant network can introduce various open doors, viewpoint of framework innovation and a remedy for the irregular idea of environmentally friendly power sources. This exposition analyzes the latest progressions in electric vehicle innovation, the impacts of their reception, and the valuable open doors they've made.

Virtual data-based generative optimization using domain-adaptive designable data augmentation (DADDA): Application to electric vehicle design

In the field of virtual product development, product performance is evaluated at an early stage through metamodel-based optimization using simulation, reducing development time and cost, and improving product quality. However, it takes a lot of time to construct a simulation model. The model must go through calibration and validation process to reduce errors with actual systems. This study proposes a novel engineering design process that can perform virtual data-based generative optimization by adapting the design domain of existing systems to those of new systems without requiring many simulations. A domain-adaptive designable data augmentation (DADDA) algorithm is proposed using inverse generator-implemented data augmentation, domain adaptation, and design optimization techniques. The DADDA algorithm can quickly provide optimal design variables for new systems compared to the genetic algorithm-based approximate optimization. The proposed process was applied to electric vehicle design. Driving responses and design variables related to safety performance were selected, and a small amount of training data was obtained using Modelica-based electric vehicle. As a result, it was shown that DADDA could significantly reduce the time required to derive optimal design variables by approximately 53% compared with the existing method. In addition, it is possible to derive the optimal performance for a new electric vehicle, which is approximately 21% better than that of an existing vehicle.

On Welding of High-Strength Steels Using Laser Beam Welding and Resistance Spot Weld Bonding with Emphasis on Seam Leak Tightness

The design of most electric vehicles provides for the positioning of the heavy energy storage units in the underbody of the cars. In addition to crash safety, the battery housing has to meet high requirements for gas tightness. In order to test the use of high-strength steels for this sub-assembly, this paper examines welded joints utilizing resistance spot weld bonding and laser remote welding, with special regard to the gas tightness of the welds. For this purpose, the pressure difference test and helium sniffer leak detection are presented and applied. The combination of both leak test methods has proven ideal in experimental investigations. For laser remote welding, gas-tight seams can be achieved with an inter-sheet gap of 0.1 mm, even if occasionally leaking samples cannot be prevented. Resistance spot welding suits gas-tight joining with both one- and two-component adhesives. Against the background of leak tightness, process fluctuations that lead to weld spatter and defects in the adhesive layer must be prevented with high priority.

Thermal performance assessment for an array of cylindrical Lithium-Ion battery cells using an Air-Cooling system

Modern society depends on energy storage systems like Lithium-ion (Li-ion) batteries. Li-ion battery cells are delicate to changes in temperature. Extreme environmental conditions affect their life cycle and performance. Therefore, effective cell temperature management is a must for secure and dependable battery operation. Additionally, the high production costs of electric cars must be countered by the adaptability of the battery pack design for modern electric vehicles. As the chemical reactions generate more heat and raise the battery's temperature, it may cause the battery to explode and cause fires in the workplace. To address this issue, the present work attempts to numerically study a novel design of an efficient air-cooling system for improving the performance of lithium-ion batteries by reducing the operational temperatures under a different coolant flow rate. The main output of the presented study is the analysis of a novel design of an efficient air-cooling system for lithium-ion batteries. The study aims to reduce the operational temperatures of the batteries under different coolant flow rates to improve their performance and service life. The numerical simulations are carried out using a finite volume-based computing tool with the K-epsilon (k-ε) turbulence model. The analysis is performed for various pertinent parametric ranges, including the spacing between the batteries, Reynolds numbers, and average Nusselt numbers. The results indicate that increasing air inlet velocity (Re) substantially reduces the average air temperature of the cooling pack and temperature difference (ΔT) of the battery cells, and the cooling pack's average heat transfer rate (Nu) increases monotonically as the Re increases.

Incorporating the best sizing and a new energy management approach into the fuel cell hybrid electric vehicle design

Under the banner of sustainable transportation, fuel cell hybrid electric vehicles (FC-HEVs) have become a matter of fascination in today's ever-growing need to save fossil fuels and reduce greenhouse gas emissions, addressing the 3Es challenges (efficiency, economy, and environment). However, one of the most pressing issues at the moment is determining how to incorporate the optimal sizing and energy management strategy (EMS) into FC-HEVs. In this regard, this article presents an integrated approach for optimal sizing as well as a new energy strategy for the design of FC-HEVs. To minimize the decision variables, including operating cost, fuel consumption, and component weight, an in-house optimization MATLAB code with a Multi-Objective Particle Swarm Optimization algorithm was developed. Four energy cases were tested under ARTEMIS and NEDC driving cycles for simulation, and their influence on the key decision variables was also investigated. The results show that using a battery pack with a supercapacitor reduces fuel consumption by 19% and 30.3% in both driving cycles, while decreasing the maximum output power of the fuel cell. It should be noted that hybrid energy sources have the potential to improve vehicle performance.

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.

Study on Multi-Objective Optimization of Power System Parameters of Battery Electric Vehicles

The optimization of power parameters is the key to the design of pure electric vehicles. Reasonable matching of the relationship between various parameters can effectively reduce energy consumption and achieve energy sustainability. In this paper, several vehicle performance indexes such as maximum vehicle speed, acceleration time and power consumption per 100 km were used as optimization target vectors, and transmission ratio was used as optimization variable to establish the optimization problem of parameter matching. Then, the feasible domain of the transmission ratio was obtained by taking the lowest performance index of the vehicle as the constraint condition. In the feasible domain, the multi-objective genetic algorithm is used to solve the optimization problem. The Pareto optimal solution set is obtained for fixed ratio transmission and two-gear transmission, which is used as an alternative solution set. The final parameter-matching scheme is determined by comparing the alternative scheme set of different motors comprehensively. The results show that the competition relationship between multiple optimizable indexes can be described effectively by solving the Pareto front. Specifically, the Pareto optimal solution set for the motor A + fixed transmission scheme is 1.33~1.85; the Pareto optimal solution set for the motor A + 2 transmission scheme is [1.72, 0.98]~[2.99, 1.57], and the Pareto optimal solution set for the motor B + 2 transmission scheme is [2.99, 1.40]~[2.99, 1.57]. The motor A + fixed transmission scheme does not require A clutch and does not require designing a shift algorithm. Therefore, after comprehensive consideration, the motor A + fixed transmission ratio transmission scheme is set as the final scheme.