Aiming at the problems of slow response speed, poor anti-interference performance, and dynamic cross-coupling of d-q axis voltage in the traditional permanent magnet synchronous motor (PMSM) control system, this paper designs the current loop with internal model control (IMC) and the speed loop with active disturbance rejection control (ADRC), and proposes an improved ADRC-IMC strategy. The IMC can effectively realise dynamic decoupling, and a low-pass filter is introduced to improve the robustness of the system. In ADRC, because the fal function is not smooth at the inflection point, the sudden change of the derivative may degrade the dynamic performance of the system. Therefore, it is redesigned to ensure that the improved fal function is continuous and derivable at the inflection point, and it is optimised with requirements of 'small error, large gain; large error, small gain'. Finally, the improved ADRC-IMC system has a faster response speed and stronger anti-interference ability.
This paper provides a comprehensive analysis of China's electric vehicle (EV) battery recycling industry, highlighting its role in promoting sustainability and innovation. As the global demand for electric vehicles escalates, effective battery recycling becomes crucial for environmental conservation and resource management. This study delves into China's pioneering efforts in establishing a robust EV battery recycling system. We explore the technological advancements, regulatory policies, and environmental impacts associated with this industry. By examining the challenges, including standardisation and recycling efficiency, the paper underscores the importance of global collaboration in advancing sustainable EV battery recycling practices. China's strategies and achievements offer valuable insights for the international community, emphasising the country's emerging leadership in sustainable EV battery management. The aim is to provide a detailed understanding of the recycling processes and their global implications, thereby fostering a more sustainable future in electric vehicle technology.
The PC-based wireless power transfer (WPT) coil design procedure is promising for complex designs and calculating the design parameters for efficient power transfer in EV systems. This work investigates the effect of the three-dimensional geometry of electromagnetic coil assemblies for transmitting and receiving coils with circular bases and compares different geometry parameters. The WPT coil was developed with the conical helix geometry, cylindrical helix, and planar coil with ferrite and aluminium shielding to provide enhanced coupling (k) along the aluminium shielding to reduce the magnetic leakage in the surroundings, assuring minimum loss and better k, self and mutual-inductance (L, M), flux density (B), and field intensity (H) with maximum efficiency. The proposed geometry also provides minimum current density and maximum flux linkage, confirming better WPT. All modelling and simulation work was conducted in the Ansys Maxwell. The circular base conical helix with shielding is promising for WPT-based EV-charging systems.
This paper presents the design and experimental study of an electromechanical braking system. Electromechanical braking is novel braking system. However, the existing systems require both amplification and motion conversion mechanisms, leading to challenges in brake force regulation. In this paper, a novel solution using linear motor is proposed. By leveraging the linear driving characteristics, the motion conversion mechanism is eliminated, leading to a simplified structure. The study employs the design of experiments (DOE) method to optimise the design parameters. The optimisation process focuses on enhancing the electromagnetic thrust, thereby improving the braking force. Subsequently, a thrust test bench and a braking test vehicle are established. The thrust test verifies that linear motor can provide sufficient thrust for braking, while the vehicle-level testing confirms that the brake unit based on linear motor can precisely and rapidly regulate the brake force, consequently shortening the braking distance and enhancing safety performance.
In this paper, a two-stage on-board charging system based on IPOP LLC resonant converter is proposed. The front stage uses a three-phase VSR, which can realize the PFC function and provide a stable DC voltage to the rear stage. The rear stage adopts IPOP LLC resonant converter, low output current ripple, output a wide range of DC voltage, the soft switch over the full load range, and the system efficiency is high. Voltage current double closed-loop control is used for the front stage converter and outputs stable DC voltage. The rear stage converter adopts variable frequency voltage regulation control and phase shift current sharing control, which reduces the volume of the filter capacitor and improves the overall performance and power density of the on-board charging system. A 3.3 kW system simulation model is built to prove the correctness of the theoretical analysis and parameter design method.
This paper proposes an efficient light spectrum optimiser (LSO) for enhancing the direct torque control (DTC) strategy for open-end winding induction motor drives used in electric vehicles (EVs). The purpose is to reduce torque and current ripples while balancing the system's power flow and increasing efficiency. The LSO algorithm is utilised to control the optimal switching states of the inverter. By integrating battery power management and LSO, the goal is to achieve more efficient energy utilisation and improved motor performance. By that point, the proposed model has been used as a working model in MATLAB/Simulink, and the execution has been computed based on the available techniques. The proposed method show's the efficiency is high, the torque and current ripples and the systems power flow are balanced compared to existing methods, like wild horse optimiser (WHO) particle swarm optimisation (PSO) and heap-based optimiser (HBO).
The air gap flux of the permanent magnet synchronous motor is constant, so the electric vehicle driven by ordinary permanent magnet synchronous motor has the disadvantages of narrow speed range and low output torque. The novel flux adjustable outer rotor permanent magnet synchronous motor by mechanical method is proposed to overcome the above shortcomings. The structure and magnetic field regulation principle of the outer rotor permanent magnet synchronous motor is introduced and analysed. The changing discipline of magnetic density distribution, flux linkage, back electromotive force, inductance and output torque are obtained based on finite element method. The change of electromagnetic characteristics at different operating speeds shows that the outer rotor permanent magnet synchronous motor has good magnetic weakening characteristics, which can promote output torque at low speed and broaden the operation range at high speed of electric vehicle.
In a brushless DC (BLDC) motor control system, Hall effect sensors usually need to provide rotor position and speed information to control the motor position and speed. Hall effect sensors are prone to errors, errors that may occur due to defects in the electrical circuit of the sensors or improper installation of the sensor. Hall effect sensor position error is one of the most common errors caused by possible manufacturing tolerances during the installation process, even if this error does not immediately lead to system failure, it has a long-term effect on the overall performance of the engine. It can also affect torque ripple. In this article, a method for placing the Hall effect sensors at inappropriate angles in the motor driver is presented, so that the effect of the position error of one Hall effect sensor, two Hall effect sensors, and three Hall effect sensors on the torque of this motor can be investigated. In fact, in this review, all types of Hall sensor position errors are evaluated. The analysis is done through simulation in MATLAB and the results are confirmed by measuring the torque ripple coefficient.
A two-stage bidirectional DC/DC converter for electric vehicles is proposed in this paper. The converter has the features of bidirectional power flow and a wide input voltage range, which can realise output voltage stability. The front stage adopts a bidirectional CLLLC resonant converter with good characteristics of soft switching in both forward and reverse directions and adopts open-loop fixed frequency control to realise efficient power transmission. The rear stage adopts an interleaved parallel bidirectional buck/boost converter to reduce the current ripple and increase the transmission power and adopts the duty cycle secondary distribution method to achieve current equalisation and regulate the output voltage based on the voltage and current double closed-loop control. Bidirectional DC/DC converter's principle analysis and parameter calculation are completed, and the correctness and feasibility of the theoretical analysis are verified by simulation results.
This manuscript proposes a hybrid approach for an autonomous vehicle (AV) control system to improve the robustness of vehicles. The proposed hybrid technique is the combination of honey badger algorithm (HBA) and radial basis function neural network (RBFNN), together known as HBA-RBFNN technique. The major purpose of the proposed method is detecting the real-time signal by detecting the intermittence and abruption amid two autonomous vehicle (AV) systems to enhance safety. The proposed approach is applied to control the speed and acceleration of the system. The distance-gap is controlled by reference acceleration by the controller of proportional integral derivative (PID). The proposed approach carries out the best tuning of the proposed approach and the control signal is produced using the HBA approach, and the best signal is predicted by using the RBFNN approach. Then, the performance of the proposed approach is done in MATLAB and compared with existing approaches. The proposed method optimally controls the vehicle and increases the robustness of the system. From the simulation outcome, the proposed method gives less settling time and is better than the existing approaches.
State of charge (SoC) is an important index of batteries and its knowledge is mandatory for an effective battery management system (BMS). There are several methods adopted for SoC estimation ranging from model-based methods to model-free methods. Among these, the model-based method with an extended Kalman filter (EKF) has gained more attention by its high accuracy. The objective of this work is to optimally tune the error covariances of EKF and then estimate the SoC. A simplified version of ant colony optimisation (ACO) is employed for optimally tuning the error covariances of EKF. The proposed ACO-based approach is lucidly explained and SoC values for three different types of dynamic drive cycles of a lithium-ion battery are estimated. The experimental results revealed a reduction in root mean square error (RMSE) from 3.06% with the conventional approach to 1.59% with the proposed method. Further experiments with varying quantities of drive cycle data revealed that the drive cycle dataset does not need to be used in its entirety and that in most cases, one-third of the data is sufficient to optimally tune the EKF parameters.
With the increasing demands for battery technology in the electric vehicle (EV) industry, a precise battery thermal management system can significantly improve the battery's performance while minimising loss and maximising efficiency. This article describes the thermal behaviour of large scale lithium-ion battery applicable for electric vehicles (EVs) and hybrid electric vehicle (HEVs). The necessity of a precise battery thermal management system (BTMS) is to maximise the efficiency of energy storage capacity, driving range, cell longevity and system safety which requires a better understanding on battery thermal distribution and behaviour. According to the requirements, this paper gathers the findings from available studies and highlights the influences of charge and discharge rate, state of charge (SOC), battery internal resistance, cooling system and thermal runaway on battery thermal distribution, behaviour and performance.
This paper deals with an inverter topology called voltage lift quasi Z-source inverter (VLQZSI), which has high implicit boost ability and is very much suitable for Electric vehicles (EVs) with fuel cells as an input energy source and 800 V motor as a driving motor. As it is a non-isolated single-stage topology, it eliminates the isolation transformer and the need for a separate DC-DC converter to adjust input voltage. The switching scheme implemented is a maximum constant boost pulse width modulation (MCB PWM). The advantage of using this scheme is that the required voltage boost can be obtained at very low duty cycle values, and hence, the modulation index will be higher, which leads to lower THD in the voltage at the output end of the DC-AC converter. The topology analysis and switching scheme are described, and the topology operation is shown through simulation results obtained from MATLAB.
A two-stage on-board DC-DC converter with a wide input voltage range and output low voltage large current is proposed in this paper. The on-board DC-DC converter consists of a front-stage buck converter and a rear-stage three-phase interleaved LLC resonant converter. The equivalent model is established by the fundamental wave analysis method, and the voltage gain characteristics and current sharing characteristics are analysed. The front-stage converter uses three closed-loop controls to convert a wide range of input voltage to a stable voltage value to the rear-stage. The rear-stage converter adopts phase shift current sharing control to ensure the current balance of each phase and reduce the output current ripple. The system model is established by using the simulation software. The simulation results verify the correctness of the theoretical analysis and the feasibility of the control strategy.
This paper focuses on various charging techniques and shares current trends that help to illustrate the effects of each charging method. The influence of charging modes is examined in a later part, along with its benefits and drawbacks. The charging processes and numerous modes, which are in charge of making sure the electric car runs well, are thoroughly discussed. The preferred method and its intended use in light of the advancements noticed in recent scenarios have also been examined further in this study. Applications of various charging modes and for smooth transition to e-mobility related advanced technologies are also thoroughly covered.
To enhance the adaptability of electric vehicles (EVs) and mitigate the intermittent nature of renewable energy sources, energy storage via batteries is imperative. Accurate forecasting of battery performance parameters is vital for optimal utilisation. This study introduces a machine learning algorithm for electric vehicle battery management systems (BMS), focusing on predicting state of charge (SoC) efficiently and precisely. Utilising linear regression and long short-term memory (LSTM) models, the algorithm constructs and deploys predictions. Training data, obtained from Li-ion battery packs during charge-discharge cycles via smart BMS, enables precise modelling. Predicted values are validated against empirical results, and the resultant error guides algorithm refinement for enhanced accuracy. The algorithm, integrated into a web application using Streamlit, achieved a remarkable 99% R2_score, indicating its robust performance. This framework advances EV battery management, facilitating informed decision-making and optimising energy utilisation in conjunction with renewable sources.
Aiming at the vibration and noise problems caused by the constant rise in speed of the permanent magnet synchronous motor (PMSM) of electric vehicles, the natural frequency of motor stator is first analysed using the lumped mass method. Simultaneously, a fast equivalent modelling approach of motor stator with winding as added mass and material anisotropy is proposed. The finite element model of PMSM is established based on the established equivalent stator model, and its natural frequency and vibration shape are investigated. Finally, the motor's modal test is carried out on the modal test platform. The results show that the difference between the natural frequency simulation and the test results is less than 3%, and that the vibration modal characteristics of each order are consistent. The feasibility and accuracy of the fast equivalent modelling method are verified, laying the groundwork for the following optimised design of PMSM vibration and noise.
