Advanced Integrated Bidirectional AC/DC and DC/DC Converter for Plug-In Hybrid Electric Vehicles

Hybrid electric vehicle (HEV) technology provides an effective solution for achieving higher fuel economy, better performance, and lower emissions, compared with conventional vehicles. Plug-in HEVs (PHEVs) are HEVs with plug-in capabilities and provide a more all-electric range; hence, PHEVs improve fuel economy and reduce emissions even more. PHEVs have a battery pack of high energy density and can run solely on electric power for a given range. The battery pack can be recharged by a neighborhood outlet. In this paper, a novel integrated bidirectional AC/DC charger and DC/DC converter (henceforth, the integrated converter) for PHEVs and hybrid/plug-in-hybrid conversions is proposed. The integrated converter is able to function as an AC/DC battery charger and to transfer electrical energy between the battery pack and the high-voltage bus of the electric traction system. It is shown that the integrated converter has a reduced number of high-current inductors and current transducers and has provided fault-current tolerance in PHEV conversion.     

Fuel cells for the long haul, batteries for the spurts [electricvehicles]

Until only a few years ago, when environmentalists, automakers, and other concerned parties spoke about low-emissions vehicles, they were almost always referring to electric vehicles (EVs)-cars, trucks, and buses powered by batteries of one kind or another. Today, having so far failed in their quest for a battery that could make EVs practical, they are looking more and more to hybrid electric vehicles (HEVs), which automakers had hitherto rejected as merely an interim solution. But hybrids based on a combination of electric motors and internal combustion engines are attractive for two main reasons: they require no technology breakthroughs and no new infrastructure. They work with existing batteries since they do not rely on them for primary energy storage; rather, they can obtain fuel at any service station. An alternative to HEVs is fuel cell powered vehicles. The principles of this technology and the associated hydrogen storage issues are discussed. Other alternative fuels are briefly outlined     

电动汽车锂离子电池荷电状态估算方法研究综述

锂离子电池具有循环寿命长、能量密度高、自放电率低、环境污染小等优点,在电动汽车产业中得到广泛应用。电动汽车中的电池管理系统(BMS)可以维护和监测电池状态,确保电池的安全性和可靠性。电池荷电状态(SoC)表示电池中剩余的电量,是BMS的重要参数之一,实时精确的SoC估算可以延长电池寿命,保障行驶安全。然而锂离子电池是一个高度复杂的非线性时变系统,电池寿命、环境温度、电池自放电等许多未知因素均会对估算精度造成影响,使估算难度大大增加。为了满足不同条件下对锂离子电池SoC精确、快速、实时估算的要求,需要对SoC估计算法进行进一步研究与改进。近年来已有相关文献对锂离子电池SoC的估算方法进行了综述,然而已有相关综述对估算方法的总结不够全面且缺少流程表达。该文首先介绍了锂离子电池的工作原理,阐述了影响电池SoC估算的因素;其次,通过总结最新的研究成果对电池SoC估算方法进行了归纳分析,根据各类算法的不同特性将其分为查表法、安时积分法、基于模型的方法、数据驱动的方法以及混合方法五大类,说明了各类估算方法的主要特征并对模型或算法的优缺点进行综合的比较和讨论;最后,对电动汽车中锂离子电池SoC估算方法的未来发展方向做出展望。     

Fuzzy Gain-Scheduling Proportional–Integral Control for Improving Engine Power and Speed Behavior in a Hybrid Electric Vehicle

With the increased emphasis on improving fuel economy and reducing emissions, hybrid electric vehicles (HEVs) have emerged as very strong candidates to achieve these goals. The power-split hybrid system, which is a complex hybrid powertrain, exhibits great potential to improve fuel economy by determining the most efficient regions for engine operation and thereby high-voltage (HV) battery operation to achieve overall vehicle efficiency optimization. To control and maintain the actual HV battery power, a sophisticated control system is essential, which controls engine power and thereby engine speed to achieve the desired HV battery maintenance power. Conventional approaches use proportional-integral (PI) control systems to control the actual HV battery power in power-split HEV, which can sometimes result in either overshoots of engine speed and power or degraded response and settling times due to the nonlinearity of the power-split hybrid system. We have developed a novel approach to intelligently controlling engine power and speed behavior in a power-split HEV using the fuzzy control paradigm for better performances. To the best of our knowledge, this is the first reported use of the fuzzy control method to control engine power and speed of a power-split HEV in the applied automotive field. Our approach uses fuzzy gain scheduling to determine appropriate gains for the PI controller based on the system's operating conditions. The improvements include elimination of the overshoots as well as approximate 50% faster response and settling times in comparison with the conventional linear PI control approach. The improved performances are demonstrated through simulations and field experiments using a ford escape hybrid vehicle.     

Reversible fuel cell enabled underwater buoyancy control

A variable buoyancy system (VBS) operated by a reversible fuel cell (RFC) with feedback depth control is developed. The system varies its buoyancy by inflating or deflating a bladder via gases produced by electrolysis or consumed through fuel cells. The system has advantages in the perspective of energy efficiency since some of the energy used for the electrolysis process is recaptured by the fuel cell. Furthermore, it is noiseless and compact, facilitating smooth integration with other underwater robots requiring buoyancy control. A PDA (Proportional-Derivative-Acceleration) feedback controller is designed to regulate the electrochemical process to position and stabilize the device at a certain depth. The model describing the VBS’s motion dynamics with bounded gas rates is used to evaluate the range of motion before instability. Then, a jerk-constrained time-optimal trajectory planner is employed to generate a suboptimal trajectory to move the VBS between two known depths. Finally, the effectiveness of the controller is confirmed with experiments. The real-time experiment shows that the controller can track both sinusoidal reference and the suboptimal trajectory planned between two depths. The device can achieve fine depth control with a depth resolution of 0.06 m, which makes its application promising in bio-inspired underwater robots.     

A feedforward controller by modified series approximation

A new pole-zero cancellation technique using a modified series approximation is proposed for the feedforward controller. The gain of the system with the proposed feedforward controller is close to 1 for up to relatively high frequency. The tracking error of this method depends on the pth-order difference of the desired trajectory. The method is effective when the closed-loop system has unstable zeros in the left-half plane of the z plane close to the unit circle. The tracking errors are analyzed in terms of the location of an unstable zero and the reference trajectory. The effectiveness of the proposed method is shown in the simulation     

Smart dual battery management system for expanding lifespan of wireless sensor node

Wireless sensor nodes have huge energy demand for their operations; they are deployed in remote locations for various applications like weather, industrial, satellite, construction, banking, and medical. Sensor nodes require continuous or uninterrupted power supply during their life cycles. When the available renewable power sources are not sufficient to run the system, the batteries are required to deliver a continuous and uninterrupted power supply. The main focus of proposed model is to design and develop a smart dual battery management system along with a hybrid energy harvesting model that can provide reliable and efficient power support to the sensor node. The problem under consideration also focuses on reducing the state of health degradation of batteries by applying a smart battery charging methodology using an ANFIS (adaptive neuro-fuzzy inference system) controller. The proposed power management system ensures and meets the expected objectives such as switching of power sources, smart battery charging methodology (constant current and constant voltage [CC-CV]), and dual battery power support using ANFIS controller. The result was obtained through the simulation and hardware prototype of the proposed system work flawlessly to meet the desired objective with partial charging and discharging of batteries for the prevention of battery degradation and also enhance the lifespan of the batteries.     

A Repetitive Model Predictive Control Approach for Precision Tracking of a Linear Motion System

In this paper, a new model predictive control (MPC) approach suitable for high precision linear motion drive operating with repetitive tracking tasks is presented. For the proposed predictive controller, the feedforward controller of the conventional MPC has been modified to provide zero-phase learning property. This is achieved by augmenting the reference trajectory with a phase-compensated term that is updated with the historical tracking error. The proposed approach attempts to combine the merits of both the conventional MPC and repetitive control schemes. Experimental results have demonstrated that the system effectively reduces the tracking error from the periodic disturbance caused by the friction. Its performance under varying reference conditions and different loadings shows that the system is robust.      

Modellierung der parallelen Antriebsstränge für ein Hybrid-Elektrofahrzeug vom Typ „Hybrid Through The Road“

Hybrid electric vehicles (HEV) are equipped with an internal combustion engine (ICE) and an electric drive (ED). They are devided into serial and parallel HEVs, depending on the power flow. The ED needs to be controlled. This allows reduction of emissions and the amount of gas. In regenerative braking, the braking energy is converted into electrical energy and fed into a battery. The fuel efficiency of the ICE in the driving state is increased by loading or uploading through ED. Cut off the ICE while standstill reduces the waste of gas. A simulation tool in MATLAB/SIMULINK calculates the amount of gas for an HEV of parallel type for a given driving cycle. The drives are considered as efficiency maps from measured data. The fuel economy of the HEV depends on the driving cycle, the vehicle mass and the engine speed while shift of gears. For a vehicle of Minivan class, the saving is between 17% up to 25% compared to a vehicle driven by an ICE only.     

Energy management strategies for vehicular electric power systems

In the near future, a significant increase in electric power consumption in vehicles is expected. To limit the associated increase in fuel consumption and exhaust emissions, smart strategies for the generation, storage/retrieval, distribution, and consumption of electric power will be used. Inspired by the research on energy management for hybrid electric vehicles (HEVs), this paper presents an extensive study on controlling the vehicular electric power system to reduce the fuel use and emissions, by generating and storing electrical energy only at the most suitable moments. For this purpose, both off-line optimization methods using knowledge of the driving pattern and on-line implementable ones are developed and tested in a simulation environment. Results show a reduction in fuel use of 2%, even without a prediction of the driving cycle being used. Simultaneously, even larger reductions of the emissions are obtained. The strategies can also be applied to a mild HEV with an integrated starter alternator (ISA), without modifications, or to other types of HEVs with slight changes in the formulation.     

Model reference adaptive predictive control for a variable-frequency oil-cooling machine

This paper develops methodologies and techniques for the design, analysis, and implementation of a model reference adaptive predictive temperature controller for a variable-frequency oil-cooling machine, suited for cooling high-speed machine tools. The oil-cooling process is modeled experimentally as a first-order system model with a time delay and its system parameters are identified using the recursive least-square method. Based on this model, a model reference adaptive predictive controller is proposed for achieving set-point tracking and robustness. A real-time model reference adaptive predictive control algorithm is then presented and implemented utilizing a stand-alone digital signal processor TMS320F243 from Texas Instruments Incorporated. The experimental results show that the proposed control method is proven capable of giving satisfactory performance under set-point changes, fixed loads, and load changes.     

A new method to estimate the state of charge of the green battery

Green batteries have attracted great attention due to the characteristics of its high performance and non-pollution. In order to understand the working condition of the batteries and get a better estimation effect on the state of charge (SoC), the following works had been done in NMC18650 lithium ion battery. Firstly, the hybrid pulse power characteristic (HPPC) test was carried out on the battery with different currents. The extended Kalman filter (EKF) was used to estimate the SoC of the battery based on combined model and Thevenin model whose parameters were identified in advance; furthermore, the estimation results of the two models were compared. Secondly, an improved open circuit voltage (OCV) based method was proposed. Its improvements were as follows: the changes of OCV on battery were recorded during the current interruption, and it was assumed that the OCV had been restored to a certain degree if the change of OCV did not exceed 0.001 V in 10 s. Finally, two new improved methods were proposed based on the combined model, and the estimation effects of the above methods were compared under dynamic condition. The results showed that the accuracy of the Thevenin model was slightly higher than that of the combined model, and the accuracies of the two improved methods were both improved. Especially the second improved method had the least error and the best adaptability; the maximum error under dynamic conditions was 3.07%, and the average error was less than 1%, which only accounted for 22.46% of the un- improved. The improved OCV based method proposed in this study is applied to the SoC estimation of batteries, which greatly improves the accuracy of the estimation; moreover, the method is easy to implement and suitable for estimating SoC in real time.     

Fuzzy-controlled Li-ion battery charge system with activestate-of-charge controller

A fuzzy-controlled active state-of-charge controller (FC-ASCC) for improving the charging behavior of a lithium-ion (Li-ion) battery is proposed. The proposed FC-ASCC is designed to replace the general constant-voltage charging mode by two kinds of modes: sense and charge. A fuzzy-controlled algorithm is built with the predicted charger performance to program the charging trajectory faster and to keep the charge operation in a proposed safe-charge area (SCA). A modeling work is conducted for analyzing and describing the Li-ion battery in charging process. A three-dimensional Y-mesh diagram for describing the charging trajectories of the proposed FC charger is simulated. A prototype of a Li-ion battery charger with FC-ASCC is simulated and realized to assess the predicted charging performance. Experiment shows that the charging speed of the proposed FC charger compared with the general one increases about 23% and the charger can safely work in the SCA     

电动车用NiMH电池SoC预测方法的探讨

NiMH电池因具有高比能量、高功率、长寿命及宽使用温度范围等优点，成为电动汽车和混合电动汽车上很有希望的动力电源。NiMH电池SoC的预测在EV和HEV上是非常必要的，它表明了还有多少能量存储在电动汽车中。综合目前国内外情况，介绍了镍氢电池的建模及SoC预测方法的进展，分析了各种方法的适用情况。     

A class of distortionless codes designed by Bayes decision theory

The problem of distortionless encoding when the parameters of the probabilistic model of a source are unknown is considered from a statistical decision theory point of view. A class of predictive and nonpredictive codes is proposed that are optimal within this framework. Specifically, it is shown that the codeword length of the proposed predictive code coincides with that of the proposed nonpredictive code for any source sequence. A bound for the redundancy for universal coding is given in terms of the supremum of the Bayes risk. If this supremum exists, then there exists a minimax code whose mean code length approaches it in the proposed class of codes, and the minimax code is given by the Bayes solution relative to the prior distribution of the source parameters that maximizes the Bayes risk     

Modeling of Zinc Bromide Energy Storage for Vehicular Applications

Energy storage devices such as lithium-ion and nickel-metal hydrate batteries and ultracapacitors have been considered for utilization in plug-in hybrid electric vehicles (HEVs) and HEVs to improve efficiency and performance and reduce gas mileage. In this paper, we analyze and model an advanced energy storage device, namely, zinc bromide, for vehicular applications. This system has high energy and power density, high efficiency, and long life. A series of tests has been conducted on the storage to create an electrical model of the system. The modeling results show that the open-circuit voltage of the battery is a direct function of the battery's state of charge (SOC). In addition, the battery internal resistance is also a function of SOC at constant temperature. A Kalman filtering technique is also designed to adjust the estimated SOC according to battery current.      

Short seeking by multirate digital controllers for computation saving with initial value adjustment

Multirate control has been proposed to reduce the real-time computation in hard disk drive (HDD) servo systems. It has been showed that computation can be saved greatly without performance degradation by using a multirate controller for track following. This paper proposes a novel method for short seeking control based on multirate track following control and initial value adjustment. This method, which uses the same multirate controller and the same servo structure as track following, adjusts the initial values of the track following controller for short seeking. Real-time computation is greatly saved in two aspects: 1) computation is saved by multirate scheme, and 2) initial value adjustment of the feedback controller makes the use of the feed-forward controller and reference trajectory unnecessary. Simulation and experimental results verify the effectiveness of the proposed method.     

Modeling and Control of PV Charger System With SEPIC Converter

The photovoltaic (PV) stand-alone system requires a battery charger for energy storage. This paper presents the modeling and controller design of the PV charger system implemented with the single-ended primary inductance converter (SEPIC). The designed SEPIC employs the peak-current-mode control with the current command generated from the input PV voltage regulating loop, where the voltage command is determined by both the PV module maximum power point tracking (MPPT) control loop and the battery charging loop. The control objective is to balance the power flow from the PV module to the battery and the load such that the PV power is utilized effectively and the battery is charged with three charging stages. This paper gives a detailed modeling of the SEPIC with the PV module input and peak-current-mode control first. Accordingly, the PV voltage controller, as well as the adaptive MPPT controller, is designed. An 80-W prototype system is built. The effectiveness of the proposed methods is proved with some simulation and experimental results.     

Influence of Battery/Ultracapacitor Energy-Storage Sizing on Battery Lifetime in a Fuel Cell Hybrid Electric Vehicle

Combining high-energy-density batteries and high-power-density ultracapacitors in fuel cell hybrid electric vehicles (FCHEVs) results in a high-performance, highly efficient, low-size, and light system. Often, the battery is rated with respect to its energy requirement to reduce its volume and mass. This does not prevent deep discharges of the battery, which are critical to the lifetime of the battery. In this paper, the ratings of the battery and ultracapacitors are investigated. Comparisons of the system volume, the system mass, and the lifetime of the battery due to the rating of the energy storage devices are presented. It is concluded that not only should the energy storage devices of a FCHEV be sized by their power and energy requirements, but the battery lifetime should also be considered. Two energy-management strategies, which sufficiently divide the load power between the fuel cell stack, the battery, and the ultracapacitors, are proposed. A charging strategy, which charges the energy-storage devices due to the conditions of the FCHEV, is also proposed. The analysis provides recommendations on the design of the battery and the ultracapacitor energy-storage systems for FCHEVs.     

A Digital Current-Mode Control Technique for DC–DC Converters

The objective of this paper is to propose a simple digital current mode control technique for dc-dc converters. In the proposed current-mode control method, the inductor current is sampled only once in a switching period. A compensating ramp is used in the modulator to determine the switching instant. The slope of the compensating ramp is determined analytically from the steady-state stability condition. The proposed digital current-mode control is not predictive, therefore the trajectory of the inductor current during the switching period is not estimated in this method, and as a result the computational burden on the digital controller is significantly reduced. It therefore effectively increases the maximum switching frequency of the converter when a particular digital signal processor is used to implement the control algorithm. It is shown that the proposed digital method is versatile enough to implement any one of the average, peak, and valley current mode controls by adjustment of the sampling instant of the inductor current with respect to the turn-on instant of the switch. The proposed digital current-mode control algorithm is tested on a 12-V input and 1.5-V, 7-A output buck converter switched at 100kHz and experimental results are presented