蓄电池快速充电模糊控制技术的研究

由于电池充电时充电电流与充电时间的非线性,采用PID、PI等传统的控制方法对充电过程进行控制的效果不佳,该文在研究镍镉、镍氢电池充电特性的基础上,提出了利用模糊控制技术对充电过程进行智能控制的方法。文中详细介绍了充电模糊控制器的设计过程,并以XC164单片机为控制核心,设计了一种针对镍镉、镍氢电池的智能充电系统,实验结果表明,该系统可对电池的复杂充电过程进行最优控制,充电快速、效率高,充电安全,不会损坏电池或缩短电池寿命,实现了充电过程的智能化控制。     

两分钟轻松搞定无线充电功能

正智能手机用起来很过瘾,但最要命的地方就是电池不给力。现在很多手机要是能用上一天就算你幸运了。于是,我们只好给手机反复插拔充电器。这时候,无线充电技术就能帮大忙。如果你经常在同一个地方给手机插上电源,就完全可以将手机搁在一块小小的充电垫上,充电垫会给电池充满电。     

基于MSP430单片机的智能锂电池充电器设计

应用MSP430单片机设计制作了智能化、低功耗、新型手机锂电池充电器,它替代了传统的充电器,能够有效地解决传统充电器在电池充电终止点之后继续对电池进行充电的问题,从而减少了安全事故的发生。     

快人一步 如何提高智能手机充电速度

正如今智能手机的电池动辄3000m Ah起步,虽然改善了续航时间,但同时也延长了充电时间。如果你想缩短充电时的等待时间,那就不妨从三个思路着手准备吧。让手机"单纯"地充电很多玩家喜欢一边玩手机(如聊微信、打游戏)一边充电,而这种操作就好像往漏水的水盆里注水,最影响充电效率。此外,手机在充电时的发热量极大,如果此时再运行游戏也会影响电池寿命。而最有效率的充电方法就是,关机或进入飞行模式(缺点是过程中无法通话和联网),让手机"单纯"地充电。     

高分问答

1.手机开机充电好还是关机充电好?答:当然是关机好了。因为开机会有电流,不稳定,所以会有烧手机或者电池的问题,这样可以最大限度地避免电磁辐射。在开机状态下充电时,只要不操作手机就没有任何不良影响。但若是接打电话、发短信、上网下载彩铃、彩信、玩游戏则     

串联锂离子电池组均衡充电方法研究

目前,制约电动汽车发展的关键难题就是串联锂离子电池组电压不均衡问题,为了提高串联锂离子电池组在充电过程中的电压一致性,设计了一种基于Buck斩波电路的串联锂离子电池组均衡充电电路.基于锂离子电池的特点对系统总体设计进行阐述,提出一种改进的能量转移型均衡电路.阐明了该电路的工作原理,给出了均衡充电电路的控制策略.实验结果表明,该均衡电路可以使单体电池电压在充电过程中得到均衡,改善电池组的充电特性,实现较好的均衡效果.     

基于模糊控制的铅酸电池充电系统研究

作为绿色环保电动汽车动力应用的主要电源之一,铅酸蓄电池的充电技术受到了工业界的广泛关注,如何研发高效、高可靠的充电器成为急需解决的关键技术.在研究铅酸电池充电特性的基础上,提出了利用模糊控制技术对充电过程进行智能控制的方法.以NE C0881单片机为控制核心,设计了一种针对铅酸电池的智能充电系统,并详细介绍了模糊控制器的设计.实验结果表明,该系统可对大容量电池的复杂充电过程进行最优控制,充电快速、效率高,充电安全,实现了充电过程的智能控制.     

Ni-MH 电池4C 充电方法研究*

利用笔者前期申请的两个相关实用新型专利技术和一个发明专利技术,提出一种4C 快速充电的方法,包括识别和判定电池是否适用4C 大电流充电、快速充电方法、快速充电的终止条件、维护性充电以及充电完成的确认等过程。经反复测试验证,该方案只需15分钟就可以使电池的充电容量达到90%以上,同时还延长 Ni-MH 电池的循环寿命。     

一种新型锂电池充电技术

针对锂电池充电速度慢,效率低,单体电池成组充电时参数差异大等问题,从充电方法、停充检测和均衡控制三方面,提出了一种新型锂电池充电技术.改进了分阶段充电方法,使充电电流符合最佳充电曲线,有效提升了充电速度,减少了电池的析气量;提出了一种依据电压变化率的停充检测方法,避免过充的同时提升了电池剩余容量(SOC);针对单体电池成组充电,提出了一种电容均衡法,利用功率开关和电容器的储能特性实现能量转移,保证了充电过程中单体电池参数的一致性.实验结果表明:充电技术提高了锂电池充电速度和效率,并保证成组充电时单体电池参数的一致性.     

多功能太阳能充电宝设计

针对现在便携式产品电池储存容量被产品尺寸制约所造成的电池续航能力不足的问题,设计了一款太阳能充电宝,以解决电池充电的问题,同时满足充电宝便携式电源的应用.本实验设计的充电宝可以兼容为多种电子设备充电.一方面利用太阳能电池板光伏效应,将其产生的不稳定的电能经由LT3652,对锂电池进行充电,并通过对太阳能光伏板最大功率跟踪,提高了充电宝使用效率.另一方面,利用ZS6288集成移动电源管理芯片,实现了常用直流充电方式,对锂电池充放电进行管理.最终的产品实现了在室内和室外两种情况下完成充电.     

An Intelligent Energy Management Mechanism for Electric Vehicles

Electric vehicles (EVs) have become increasingly popular all over the world in recent years. Many countries have been offering reward policies and facilitating the establishment of EV charging stations and battery exchange stations to encourage use of these vehicles by the public. However, in terms of electricity demand, the rapid establishment of EV charging stations and battery exchange stations may lead to significant increases in peak loads, the contracted capacities, and basic electricity charges. In this work, an intelligent EV energy management mechanism is proposed to make use of scheduling systems for the charging stations in order to determine when to store electricity in batteries according to the real-time electricity price and the recharging requirements of EVs. Meanwhile, a recharging suggestion module is presented in this work for locating the most suitable charging station or battery exchange station for an EV according to the available information on hand. When an EV cannot reach any charging station because it is running out of electric power, a mobile CV management module is used to assist the EV to find a suitable mobile CV for recharging. Notably, a well-known machine learning technique, multiobjective particle swarm optimization, was employed in this work to assist in solving the multiobjective optimization problems during the design of an energy management mechanism. The experimental results show that the proposed mechanism can balance the loading of battery charging and exchange stations, and lower the load peak to keep electricity cost down. Meanwhile, the recharging suggestion module can decrease the driving distance of EVs for finding the charging stations, as well as decreasing the waiting time wasted while charging. The mobile CV management module, for its part, can effectively prevent EVs from becoming stranded on the road because they have run out of electricity.     

基于温差发电的车载手机充电装置设计

本文计以温差发电为基础,汽车热源（如发动机,排气管）为载体,AT89C52单片机为控制核心,设计了一款车载手机充电装置。该装置主要由温差发电片、LM2577升压稳压电路、AT89C52、MAXl898充电电路和DS2438检测电路等模块组成。该装置通过温差模块直接将汽车余热转换成电能,通过以AT89C52单片机为核心的充电模块对手机电池进行充电。     

由KSWeb构建的智能充电管理系统设计

针对传统充电管理系统使用麻烦、安全性不高等诸多问题,提出一种基于KSWeb的智能充电管理系统的思路.在小区局域网的WiFi范围内,以Android手机为控制核心,通过KSWeb构建PHP服务器,对外提供用户充电服务.服务器接收到用户发出的指令后,通过HC 06蓝牙模块与底层STC89C52进行通信,并控制相应线路的定时通断.实践表明,该系统具有使用便捷、安全性高、成本较低等优点.     

Human–battery interaction on mobile phones

Mobile phone users have to deal with limited battery lifetime through a reciprocal process we call human–battery interaction. We conducted three user studies in order to understand human–battery interaction and discover the problems in existing designs that prevent users from effectively dealing with the limited battery lifetime. The studies include a large-scale international survey, two long-term field trials including quantitative battery logging and qualitative inquiries, and structured interviews with twenty additional mobile phone users. We evaluated various aspects of human–battery interaction, including charging behavior, battery indicators, user interfaces for power-saving settings, user knowledge, and user reaction. We find that mobile phone users can be categorized into two types regarding human–battery interaction and often have inadequate knowledge regarding phone power characteristics. We provide qualitative and quantitative evidence that problems in state-of-the-art user interfaces have led to under-utilized power-saving settings, under-utilized battery energy, and dissatisfied users. Our findings provide insights into improving mobile phone design for users to effectively deal with the limited battery lifetime. Our work is the first to systematically address human–battery interaction on mobile phones and is complementary to the extensive research on energy-efficient design for a longer battery lifetime.     

基于UML的计费网关的设计与实现

计费网关是移动通信核心网络中的重要设备.它一般是集中式而且独立的网络设备,其主要负责采集来自各计费节点的计费数据,并且对计费数据进行过滤、合并、分发和传输等各项预处理,计费网关最终将计费数据提交给后续的计费系统进行批价处理.计费网关设备的引入大大简化了移动核心网络的拓扑结构,同时也减轻了计费系统的负载.     

PXA270的电池充电及电量计量模块设计

以PXA270芯片为处理器,利用2种高性能芯片 LM3658和 DS2786设计了电池充电与电量计量模块。该模块可以运用于手机、PDA、数码相机、MP3等手持设备中,能够在满足充电任务的同时,实时精确地计量当前的剩余电量,并显示在用户界面上,方便用户使用,具有很好的应用前景。     

一种智能无线充电系统设计

针对目前市场上存在的大部分无线充电系统充电效率低、充电电量可控性差等问题,文章设计了一种全新的智能无线充电系统。该系统在电池模块中嵌入电量采集模块、低功耗主控芯片和2.4G通信模块,充电模块中嵌入同样的主控和通信模块。充电模块可通过2.4G无线通信接收电池的实时电压和充电电流等信息,根据内置的智能算法,通过振幅调制载波功率限制,实现自适应动态输出。实验表明,在有效距离内,该系统具有较高的充电效率,具体充电情况可根据电池实时电量信息进行智能控制,有效地预防了电池过充和过放等问题。该智能无线充电系统具有低功耗、转换效率高、能够对充放电智能管理等特点,可广泛应用于智能家居、智能医疗、智能穿戴等领域,具有良好的社会价值和经济价值。     

Dynamic data mining technique for rules extraction in a process of battery charging

Battery charging controllers design and application is a growing industry direction. Fast and efficient charging of battery packs is a problem which is difficult and often expensive to solve using conventional techniques. The majority of existing works on intelligent charging systems are based on expert knowledge and heuristics. Not all features of the desired charging behavior can be attained by the hard-wired logic implemented by expert generated rules. Because the battery charging is a highly dynamic process and the chemical technology a battery uses varies significantly for different battery types, data mining technique can be of real importance for extracting the charging rules from the large databases, especially when the charging logic is to be continuously changed during the life of the battery dependent on the type and characteristics of the battery and utilization conditions. In this paper we use soft computing-based data mining technique for extraction of control rules for effective and fast battery charging process. The obtained rules were used for NiCd battery charging. The comparative performance evaluation was done among the existing charging control methods and the proposed system, which demonstrated a significant increase of performance (minimum charging time and minimum overheating) using the soft computing-based approach.     

Autonomous battery management for mobile robots based on risk and gain assessment

Battery management of mobile robots is an issue that has not been a strong focus of attention and is usually addressed by the simple use of battery thresholds. One of the main causes is that no significant method of assessment of risk of battery depletion has yet been proposed. As a result decision of redirection to a charging station is fixed and takes into account neither a dynamic evaluation of the risk of battery depletion nor an evaluation of the gain, defined as the level of mission accomplishment that could be achieved. In this paper we propose a novel method for evaluation of risk of battery depletion for mobile robots. Uncertainties concerning effective battery capacity, current discharge rate and energy required for reaching the station are addressed by the use of probability density functions. This risk assessment will allow replacing the usage of battery threshold by a customizable risk-taking parameter that will be used to define what level of gain is required for balancing a given level of risk. This risk/gain management of battery will guarantee that decision of redirection to the station corresponds to a favorable compromise between risk and level of mission accomplishment. While the proposed approach has been tested using a simulated and real room cleaning robot, it could be applied on a wider range of mobile robots.