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Wireless charging system for vehicular power batteries is becoming more and more popular. As one of important issues, charging power regulation is indispensable for online control, especially when the distance or angle between chassis and ground changes. This paper proposes a novel power regulation method named Z-Source-Based Pulse-Amplitude-Modulation (ZSB-PAM), which has not been mentioned in the literatures yet. The ZSB-PAM employs a unique impedance network (two pairs of inductors and capacitors connected in X shape) to couple the cascaded H Bridge to the power source. By controlling the shoot-through state of H bridge, the input voltage to H bridge can be boosted, thus the transmitter current can be adjusted, and hence, charging current and power for batteries. A LCL-LCL resonant topology is adopted as the main transfer energy carrier, for it can work with a unity power factor and have the current source characteristic which is suitable for battery charging.

The proton exchange membrane fuel cell (PEMFC) system has emerged as the state-of-art power source for the electric vehicle, but the widespread commercial application of fuel cell vehicle is restricted by its short service life. An enabling high accuracy model holds the key for better understanding, simulation, analysis, subsystem control of the fuel cell system to extract full power and prolong the lifespan. In this paper, a quasi-dynamic lumped parameters model for a 3kW stack is introduced, which includes filling-and-emptying volume sub-models for the relationships between periphery signals and internal states, static water transferring sub-model for the membrane, and empirical electrochemical sub-model for the voltage response. Several dynamic experiments are carried out to identify unknown parameters of the model.

Parallel-connected modules have been widely used in battery packs for electric vehicles nowadays. Unlike series-connected modules, the direct state inconsistency caused by parameter inconsistency in parallel modules is current and temperature non-uniformity, thus resulting in the inconsistency in the speed of aging among cells. Consequently, the evolution pattern of parameter inconsistency is different from that of series-connected modules. Since it’s practically impossible to monitor each cell’s current and temperature information in battery packs, considering cost and energy efficiency, it’s necessary to study how the parameter inconsistency evolves in parallel modules considering the initial parameter distribution, topology design and working condition. In this study, we assigned cells of 18650 format into several groups regarding the degree of capacity and resistance inconsistency. Then all groups are cycled under different environmental temperature and current profile.

Nowadays, wireless power transfer (WPT) gradually prevails and many researchers have devoted themselves to it because it is a safe, convenient and reliable way for recharging electric vehicles comparing to the conventional plug-in contact-based methods. Square coils are commonly used in WPT systems. However, there is few theoretical analysis of self- and mutual inductance of square coils between two magnetic shielding materials. In this paper, in order to study the spatial magnetic field distribution, the analytical model of n-turn square planar spiral coils between two semi-infinite multilayer media is developed based on the Maxwell equations and the Dual Fourier transformation. And then, by means of surface integrals, the self- and mutual inductance can be carried out, with respect to the main parameters of the WPT systems such as the operating frequency, the geometry feature of the coupling coils and the properties of the multilayer media.

To monitor and guarantee batteries of electric vehicles in normal operation, battery models should be established primarily for the further application in battery management system such as parameter identification and state estimation including state of charge (SOC), state of health (SOH) and so on. In this paper, an improved battery modeling method is proposed which is based on the recursive least square (RLS) algorithm employing an optimized objective function. The proposed modified objective function not only includes the normal sum of voltage error squares between measured voltage and model output voltage but also introduces a new variable representing the sum of first order difference error squares for both kinds of voltages. This specialty can undoubtedly guarantee better agreement for the measured output and the model output. The battery model used in this paper is selected to be the conventional second order equivalent circuit model.

An alternating current (AC) heating method for a NMC lithium-ion battery with 8Ah capacity is proposed. The effects of excitation frequency, current amplitudes, and voltage limit condition on the temperature evolution are investigated experimentally. Current amplitudes are set to 24A(3C), 40(5C), and 64A(8C), and excitation frequencies are set to 300Hz, 100Hz, 30Hz, 10Hz, 5Hz, and 1Hz respectively. The voltage limitations are necessary to protect cells from overcharge and over-discharge. Therefore the voltage limit condition (4.2V/2.75V, 4.3V/2.65V, and 4.4V/2.55V) are also considered in depth to verify the feasibility of the AC heating method. The temperature rises prominently as the current increases, and the decrement of frequencies also lead to the obvious growth of battery temperature. The battery obtain the maximum temperature rise at 64A and 1Hz, which takes 1800s to heat up the battery from -25°C to 18°C.

Electrochemical Impedance Spectroscopy (EIS) is often applied to analyze and describe the battery internal electrochemical processes. And the methods of battery state estimation including state of health diagnosis with electrochemical impedance have attracted a wide attention. In the paper, a novel fast impedance measuring method based on wavelet transform with a step excitation current is proposed and further studied. With the method, the current generated by the electric vehicle and the responding voltage of the battery can be utilized to calculate and provide the battery impedance for the battery management system. Taking into account the varying amplitude of the current and the battery states, the battery impedance was measured with step excitation signals of different amplitude at different temperature and state of charge (SOC).

For balancing Li-ion battery cells connected in series and effectively improving the consistency of the cells, a bi-directional equalization system based on fly-back transformer is proposed. Unlike the passive equalization technology using a resistor or active equalization with expensive DC-DC converter for the balancing among the cells, this equalization circuit consists of the fly-back transformer and RCD circuit, which can easily and cheaply realize the energy transfer between the whole battery module and the cells, and thus achieving bidirectional equalization. In this system, both the primary side and the secondary side of multi-winding transformer are connected to a MOSFET. All MOSFETs are controlled by the PWM signal. The control timing and duty ratio of the PWM control signal are determined through the simulation analysis. Meanwhile, an RCD circuit is applied at the primary side of multi-winding transformer for buffering the peak voltage caused by leakage inductance.

For a practical pad design, a magnetic shielding layer is imperative which is made of ferrite, aluminum or some other metallic material. However, once the magnetic shielding layer is added, not only the mutual inductance but also the self-inductance of the coupling coils vary with the lateral misalignment which is inevitable for a human driver. The change of self-inductance will also result in the mistuning problem in the resonant circuit, which can significantly reduce the transmission efficiency of the whole wireless power transfer (WPT) system. This paper proposed a method of parameter identification of self-inductance based on the least square in order to solve the mistuning problem. In order to verify the proposed method, both the simulation model and the experiment set-up are built.

The automotive industry is evolving towards Electrified Vehicles (EV) in the recent years. Compared to the traditional ICE vehicles, tire noise induced by the tire-road interaction, is no longer masked by the internal combustion engine, and therefore becomes one of the most dominant sources of noise within the cabin and acoustic emission perceived by by-standers. Robust source characterization is one of the most important tasks for road noise prediction. The receiver-independent tire blocked forces are often used as ire-road source characteristics, which can be applied to any test-based or FE-based vehicle model to obtain the interior noise. They can be inversely identified from measurements on a tire test rig or on an in-situ vehicle. However, this inverse process needs to be repeated for different tires, roads and rolling speeds, which can become time-consuming and expensive.

With the degradation of lithium-ion batteries, the battery safety performance changes, which further influences the safe working window. In this paper, the pouch ternary lithium-ion battery whose rated capacity is 4.2 Ah is used as the research object to investigate the impact of the high-temperature calendar and cyclic aging on tolerance performance. The overcharge-to-thermal-runaway test is performed on the fresh cell and aged cell (90% SOH). The inflection point of voltage for aged cells appears earlier than that of the fresh cell, while the voltage corresponding to the inflection point is the same for them, which means that the voltage at which lithium plating occurs is the same. However, the voltage plateau and the crest voltage before thermal runaway of aged cell are significantly higher than that of the fresh cell. Besides, ohmic heat, reversible heat, and side reaction heat make contribution to the thermal runaway triggering.

Focusing on distributed electric vehicles with in-wheel motors, a novel regenerative braking control strategy based on braking intention is proposed. Firstly, a design scheme for the regenerative braking system is described. Four in-wheel motors and an Electro-Hydraulic Braking (EHB) system are respectively designed for regenerative braking and hydraulic braking. Then, Braking intention recognition self-learning libraries are trained based on Hidden Markov Model method, which is validated by driver-in-loop tests. According to three speed states and four braking intentions, the regenerative braking control strategy for multiple brake modes is developed. The coefficient of regenerative braking is defined to describe the intervening time and proportion of motor maximum regenerative braking.

As the core component of electric vehicles (EVs), batteries attach increasingly general attention along with the rapid expansion of electric vehicle market. Battery performance effect directly the safety and reliability of the EVs, so its managing technologies are more and more crucial. Among them, the methods of estimating the state of health (SoH) and predicting remaining useful life become the focuses, which are essential to ensure their dependability and optimum performance over time. This paper mainly focuses on impedance modeling and aging research (aging diagnosis and life prediction) of lithium-ion batteries. Electrochemical impedance spectroscopy (EIS) technique is used to obtain impedance characteristic of batteries. On the one hand, equivalent circuit modeling (ECM) can be motivated by EIS, with the goal to fit measured impedance data using circuit elements.

State-of-Power (SoP) prediction of Li-ion battery is necessary in battery management system for electric vehicles in order to deal with limited conditions, prevent overcharge and over discharge situations, increase the life of the battery and provide effective battery operation. This article suggests a method to on-line predict the 10-s charge and discharge peak power of Li-ion battery by twice recursions. First with the dynamic battery model we use the first recursion based on a least square method to get parameters which are influenced by the state of charge of Li-ion battery and temperature, etc. The dynamic model is an equivalent circuit model. Current and voltage are input online into the battery model. By recursive least square method the parameters are updated in real time. Moreover, when we use a recursive method to get real-time parameters, we add an extra proper factor to abandon old datum, which increases the real-time capability of state-of-power prediction.

This paper aims at accurately modeling the nonlinear hysteretic relationship between open circuit voltage (OCV) and state of charge (SOC) for LiFePO4 batteries. The OCV-SOC hysteresis model is based on the discrete Preisach approach which divides the Preisach triangle into finite squares. To determine the weight of each square, a linear function system is constructed including a series of linear equations formulated at every sample time. This function system can be solved by computer offline. When applying this approach online, the calculated square weight vector is pre-stored in advance. Then through multiple operations with hysteresis state vector of squares updated online at every sampling time, the SOC considering the influence of OCV-SOC hysteresis is predicted.

Lithium-ion battery charging strategy affects charging time of electric vehicles, energy efficiency of entire vehicle, service life and safety. This paper focuses on the lithium iron phosphate (LiFePO4) battery, based on the battery internal mechanism and the working conditions, taking charging time, effective full-charge capacity and charge energy efficiency as the evaluation indexes. Firstly, through a series of comparative experiments of the constant-current constant-voltage and the constant current charging strategy, the evaluation indexes variations in different temperatures and charging currents have been studied in the paper. By analyzing the respective characteristics of constant current charging phase and constant voltage charging phase in the whole charging process and their own contributions, we have found out the superiority of the constant current charging strategy.

Analogous to a vacuum boosted system, Electro-Hydraulic Braking System (EHB) is free from engine vacuum and supplies a braking force proportional to driver input. The independence of engine vacuum makes it especially suitable to be used in electric vehicles (EVs) and hybrid electric vehicles (HEVs). As a key component of EHB, master cylinder is driven by the pump rather than the vacuum booster. Even if the pump fails, the cylinder can also build proper pressure. Meanwhile, in order to maintain the pedal feeling, a pedal stroke simulator is applied in the system. In this paper, aiming at decreasing the size and cost of master cylinder and providing an ideal pedal feeling without compromise of performance, a new integrated master cylinder of EHB system is designed including two parts: master cylinder and pedal stroke simulator. The key components of the integrated master cylinder are motor pump, solenoid valves and composite springs.

This paper presents a three-dimensional electrochemical electrode plate pair model to study the effect of the electrode tabs configuration. Understanding the distribution of current density, potential and heat generation rate is critical for designing li-ion batteries and conducting effective design optimization studies. We developed several electrode plate pair models which were different in position and size of tabs. Results showed the influence and comparison of different configuration on the distribution of current density, potential density and heat generation rate at different discharge process. The distribution was predicted as a function of tabs. It can provide a theoretical basis for improving battery thermal performance and cooling system design.

Regarding the lithium-ion batteries used in the electric vehicle, charging time and charging efficiency are the concern of the public. In this paper, a lot of experiments were conducted to investigate the common charging strategies, including the CC-CV (constant current-constant voltage) charging and the pulse current charging, for the LiFePO4 batteries, which are still widely used in commercial vehicles. Charging temperature and the charging current in the CC phase are the main influence factors to be studied for the CC-CV charging strategy, and the contribution of the CC phase and CV phase to the whole charging is analyzed from three aspects, including the time percent, charging energy efficiency and the capacity of battery at different temperatures and charging current.

Range anxiety problem has always been one of the biggest concern of consumers for pure electric vehicles. Accurate driving range prediction is based on accurate lithium-ion battery pack SOC (State of Charge) estimation. In this article, a complete SOC estimation algorithm is proposed from cell level to battery pack level. To begin with, the equivalent circuit model (ECM) is applied as the model of battery cell. ECM parameters are identified every 10% SOC interval through genetic algorithm. The dual extended Kalman filtering (DEKF) algorithm is adopted for cell-level SOC and ohmic resistance R0 estimation. The estimation accuracy of cell SOC and R0 is verified under NEDC dynamic working condition. The cell-level SOC estimation error is below 1%. However, cell inconsistency can always result in inaccurate cell SOC estimation inside the battery pack. The impact of initial SOC inconsistency and internal resistance inconsistency between cells on battery pack SOC is specifically analyzed.