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Description
SKY RC Q200 Neo AC/DC Quad Battery Balance Charger SK-100197SKY RC Q200 Neo AC DC Quad Battery Balance Charger Introducing the SKY RC Q200neo AC DC Charger. Quadruple the Power: Impressively Powerful, Impossibly Accurate! Experience a revolutionary charging process tailored for RC enthusiasts with the SkyRC Q200neo charger, boasting four impressive charging ports. This advanced powerhouse redefines convenience by enabling four simultaneous charging of multiple chemistry batteries and powering with dual AC DC
SKY RC Q200 Neo AC/DC Quad Battery Balance Charger
Introducing the SKY RC Q200neo AC/DC Charger.
Quadruple the Power: Impressively Powerful, Impossibly Accurate!
Experience a revolutionary charging process tailored for RC enthusiasts with the SkyRC Q200neo charger, boasting four impressive charging ports.
This advanced powerhouse redefines convenience by enabling four simultaneous charging of multiple chemistry batteries and powering with dual AC/DC input.
It delivers a remarkable total power of up to 400W with up to 10A per port. Additionally, it accelerates the balancing process among battery cells with an 800mA balancing current per cell, significantly enhancing the overall charging efficiency. The built-in high-precision balancer ensures exceptional accuracy with a remarkable voltage equalization optimization of ±0.02V.
Whether you're a seasoned professional or a passionate hobbyist, Q200neo guarantees that your batteries will always be ready to power your thrilling RC adventures.
Bid farewell to downtime and embrace the limitless potential of your RC pursuits with the SkyRC Q200neo charger.
Let the thrilling begin!
Qute Yet Mighty: Unleash Power on the Go!
Qute /kjuːt/. adjective
possessing quadrupled power or capabilities while having an appealing, cute shape or appearance.
It is used for concepts of power and cuteness.
Q200neo packs outrageous performance, 4 independent ports, and AC/DC dual input into an unbelievably compact footprint, 60% smaller than its predecessor, Q200.
Whether you need to power up your RC car, fly a drone, or use ChatGPT on your new Mac, Q200neo has you covered!
Hero Meets Hero. This is the charger made for you—the pro!
Innovation in Indigo: Immerse yourself in the cutting-edge with the SkyRC Q200neo, now available in a captivating indigo colour.
Inspired by Silicon Valley legend SGI, who famously adopted indigo for their iconic products, this vibrant hue represents innovation and pushes the boundaries of what's possible. You're not only choosing a colour, but also joining a lineage of trailblazers who refuse to settle for mediocrity.
Do More With One Charger! Multiple Chemistries Go.
With exceptional versatility, Q200neo can charge a wide range of battery chemistries. This powerhouse can charge from LiPo and LiFe to Li-ion, LiHV, Pb, NiMH, and NiCd.
You are turbocharging your time with a single charger that can handle multiple battery types.
Whether you're an RC guru, a beginner, or somewhere in between, Q200neo is the reliable and adaptable choice that ensures optimal performance for all your batteries.
Unlock the full potential of your battery arsenal with Q200neo – versatility multiplied capability.
Dual AC/DC Input: Efficient. Beyond.
Q200neo is designed to provide RC enthusiasts unparalleled flexibility in the garage or out in the field. You have the freedom to choose between AC or DC input based on your specific scenarios.
In AC mode, the charging power reaches an impressive overall 200W, dynamically distributing to each port. When powered by DC, the charger unleashes its true potential, offering an astounding overall 400W of charging power. With a single port capable of reaching up to 100W, you can power up your batteries with remarkable speed and precision.
Whether you are a beginner or a seasoned RC guru engaging in racing, Q200neo ensures efficient charging and optimal performance for your RC batteries.
Smart Power Distribution Seamless Charging Flexibility.
Under AC input, when a single two ports are in use, Q200neo will provide maximum power output to that specific ports. The charging power is distributed dynamically and intelligently when all four ports are simultaneously in use.
Once a particular port has completed its charging task, the remaining port(s) will receive increased power for faster charging. This intelligent and efficient allocation of power ensures optimal utilization at all times.
The charging capabilities of Q200neo are highly flexible, allowing for versatile charging options.
Unmatched Charging, Impressive Discharging.
This cutting-edge charger not only offers efficient charging but also provides impressive discharging functionality. The built-in balance port enables Q200neo to discharge faster, allowing it to discharge at up to 25W when used in conjunction with the main port. In contrast, the discharge rate when using the main port alone is limited to 5W.
Whether you need to prepare your batteries for storage, balance their voltage levels, or safely discharge them after use, the Q200neo is there for you! This advanced discharging feature allows you to maintain the health and longevity of your batteries by precisely controlling the discharge process.
So. Pro. So is Digital Power
Q200neo excels not only in charging, but also as a versatile quad output digital power supply.
With just a few clicks on the menu, Q200neo offers a voltage option, from 1.0V to 30.0V, with an adjustable increment of 0.1V. Additionally, the current can be adjusted from 0.1A to 10.0A, with a precision of 0.1A.
This quad output digital DC power supply provides four independently controllable power outputs, making it a versatile tool for various RC testing and prototyping applications.
20W PD 3.0 Port. Energize with Rapid Power Delivery!
With the 20W USB-C PD 3.0 charging port, our RC players can enjoy rapid charging speeds like never before. Whether you're charging your smartphones, tablets, or 2020 MacBook Airs, this powerful port ensures that you can fuel up your devices in a fraction of the time.
Multiplied by Proprietary HyperBoost
Thanks to the 200 MHz ARM Microcontroller, the deployed Oversampling Technology can improve ADC Resolution to 16bit.
The efficient PID mechanism can fine-tune the current to increase response speed and the charge current accuracy.
Charge It Cool.
Within the sleek enclosure lies a ground-breaking thermal system designed to let Arm Cortex-M4 fly through heavy workloads at screaming-fast speeds — and stay whisper quiet. The fan will adjust the speed accordingly and dissipate heat more effectively according to the different power usage.
Charge in Your Language
ColorX is designed to be easily localized and comfortably engaged. The interface is currently available in English, Dutch, Chinese, French and Japanese*. Users can easily change the language with simple clicks so that they can charge in the most comfortable language.
Universal Voltage. Travel On the Go.
With the universal-voltage input circuit, you don't need to hassle finding a voltage converter between 110V and 220V while traveling around!
Enhanced Protection, Assured Safety.
The SkyRC Q200neo charger is built-in with several essential safety features ensuring optimal charging safety.
Rectifier Circuit Efficiency Multiplied.
The Q200neo uses a proprietary rectifier circuit to efficiently convert DC into safe D/C power for battery charging. And its onboard MCU precisely controls the charging to minimize power loss to create an incredibly compact form factor.
Smart Charging at Your Keyboard or Fingertips
Connected effortlessly to your charger via the versatile Type-C port or through the convenience of Bluetooth, Q200neo can be controlled by Charger Master on PC, Mac or smartphone.
Whether you're at your keyboard or on the go, our charger puts the power in your hands.
The app empowers you to take complete charge of your charging experience.
From adjustable charging rates to battery health monitoring, you can customize every aspect of the charging process to ensure optimal performance and battery longevity.
Don't settle for ordinary boring charging. Take charge. Power up!
Stay Updated, Always!
Upgrading your charger is now easier than ever. With the Charge Master app, you have two convenient options: Connect your charger to the app using the Type-C port for a fast and reliable upgrade experience. Alternatively, you can perform an Over-The-Air (OTA) update directly through the built-in Bluetooth functionality. Whichever you prefer, upgrading your charger is a breeze.
Experience flexibility and compatibility with the Charge Master app, available in four flavors: Mac, Windows, iOS, and Android!
Stay connected, stay updated, and you deserve a happier charging experience.
We are Certified, We are Qualified!
Our products are designed, tested, and approved to meet worldwide standards for Product Safety, Electromagnetic Compatibility, and other regulatory compulsory requirements.
They are intended for use in accordance with their designated purpose.
Specifications
Size and Weight:
Case Material: PC-ABS V0
Case Size: 123*119*78mm
Weight: 680g
Display:
Display Type: TN
Size: 2.8 inch
Panel Active Area: 43.20*57.60mm
Resolution: 240x320 Pixel
Number of Colours: 262K
Power
DC Input Voltage: 10-30V
AC Input Voltage : 100-240V
Charger power:
AC: 200W MAX
DC: 400W MAX
Discharge power:
Main port: 5W
Balance port: 25W MAX (LiPo/6S)
20W USB-C Power Delivery:
QC3.0: 5V⎓3A, 9V⎓2A, 12V⎓1.5A 18W
PD: 5V⎓3A, 9V⎓2.2A, 12V⎓1.67A 20W
DC Power Supply
Output Voltage: 1.0-30.0V
Output Current: 0.1-10.0A
Output Power: Max. 100W single port
Battery
Battery Types/Cells:
LiPo/LiHV/LiFe/LiIon: 1-6cells
NiMH/NiCd: 2-15cells
Pb: 3S/6S/12S
Charge and Discharge
Charge current
LiPo/LiFe/LiIon/LiHV/NiMH/NiCd/Pb：0.1-10.0A
Discharge current
LiPo/LiFe/LiIon/LiHV/NiMH/NiCd/Pb：0.1-2.0A
Balance current
LiPo/LiFe/LiIon/LiHV：800mA MAX
Operation
LiPo/LiFe/LiIon/LiHV: Balance CHG, Charge, Storage Discharge
NiMH/NiCd: Charge, Re-Peak, CYCLE_C_D, CYCLE_D_C, Discharge
Pb: Charge, AGM Charge, Cold Charge, Discharge
Shipping Notes
- Free Standard Shipping on $100+ Orders to the USA.
- Except Preorder products are shipped in 48 hours.
- Delivery to the USA:
- Standard Shipping : 3-10 business days
- If time is of the essence, please consider selecting expedited delivery for faster service.
Exchange/Return Notes
- We offer a 30-day return/exchange service after receiving.
- Final sale items are not eligible for returns or exchanges.
- To process your return/exchange, please contact us at [email protected]
- Please click here for more details>>> Return & Exchange Policy
4.7 ★★★★★
Based on 1041 reviews
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Product Reviews
★★★★★ 5
Excellent book, possibly currently unique in coverage of latest ideas
This book is possibly currently unique in its coverage of the latest ideas in the field of deep learning -- and it is a very convenient and good survey of fundamental concepts (linear algebra, optimization, performance metrics, activation function types), different network types (multi-layer perceptron, convolutional neural networks, and recurrent neural networks), practical considerations (data set, training and validation, implementation), and applications (comments on existing real-world/commercial uses). The final 235 pages of the content portion of the book is dedicated to topics in "Deep Learning Research", and these topics are truly at the current frontier.
Another reviewer said that one could gain the same knowledge of cutting-edge research by reading all of the latest papers (from academia and industry), but the "research" section of this book offers the following: Selection of the most notable research by the very experienced authors of the book, and collection of similar research in to a broader discussion of themes, and the additional insights. The book covers very advanced and new ideas currently being explored, and it is very nice to be able to have a consistent and coherent presentation of all of those ideas.
However, the book is also packed with valuable observations and pointers about more basic aspects of deep learning implementations and practices -- and such commentary is in depth and includes substantial analysis and mathematical derivation (in an intuitive presentation that often includes graphs illustrating the phenomenon).
As someone with an intermediate level of knowledge and experience of neural networks, I am really grateful for this book, because seems like the ideal resource for learning cutting-edge ideas and practices, with context. The book has excellent scope and depth, and I am confident that anyone with a solid background in linear algebra, calculus, statistics, and general machine learning, and basic neural networks (multi-layer perceptrons) will find this book to be very exciting and perhaps unique in its ability to take the reader to the next level and a new frontier. I was personally excited to learn about the idea of representing the dependencies of intermediate quantities by directed graphs, and how this can be used to perform calculations for recurrent neural networks efficiently. And I think the long chapter on recurrent neural networks is very helpful.
Having said all of this, I think only people with significant working knowledge and experience with neural networks and mathematics -- people whose academic or professional focus has been neural networks for at least a year or two -- would benefit from this book. This book answers a lot of the deeper questions that one is likely to have while developing a solid understanding of the fundamentals, and that's one of the book's tremendous values, but this book assumes an understanding of the fundamentals (but does briskly cover the basics).
I think this book is a perfect follow-up book for the excellent book "Neural Network Design (2nd edition)" by Hagan, Demuth, Beale, and de Jesus, and I highly recommend the latter for gaining the solid background needed to have a thrilling experience with the "Deep Learning" book.
In summary, I am very glad this "Deep Learning" book was written, and I think the "Deep Learning" book will be a great benefit to a lot of people, and to the evolution of the field.
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Reviewed in the United States on April 18, 2017
★★★★★ 5
The definitive guide to becoming a researcher in the field
Format: Hardcover
This is not a coding book. I see a lot of negative reviews around the expectation that this book would teach the reader how to quickly build machine learning systems and write code. This book is not for that audience.
If you just want to build applications, don't worry about how deep learning works. It's akin to needing to understand how an engine works just to drive a car. If you are looking for a coding resource, try: https://www.amazon.com/Hands-Machine-Learning-Scikit-Learn-TensorFlow/dp/1492032646/ref=sr_1_4?keywords=machine+learning+tensorflow&qid=1579608765&sr=8-4 . And even with that book, the material still goes far beyond what you need - use it as a light reference.
I bought this book as an aspiring machine learning researcher, and towards that end, it is the best resource available in print (still true as of 2020). For instance:
The first 5 chapters are timeless. These are things that were mostly established 20 or 30 years ago and beyond and are mostly STEM fundamentals at this point. There are whole textbooks dedicated to each of those chapters, but the authors provide a quick refresher and overview of probably 80% of what you'll encounter in deep learning. If you haven't previously learned each of these subtopics, you'll probably want to study them individually since they are the key to innovating (linear algebra, probability & stats, numerical computation, machine learning fundamentals).
Chapters 6 thru 9 are the foundation of deep learning. We're about 12 years into seeing rapid change in the deep learning space, yet all of these principles and techniques still hold (many recent innovations are still relying on Convolutional models in 2020, which is the most layered/complex topics in those chapters). Therefore, I'd wager that these chapters are also fairly stable knowledge that is worth internalizing if you want to be deeply involved in the future of machine learning.
Chapters after 9 are mostly experimental topics, and many of them are already the wrong strategies for optimal results. But there are interesting ideas in here that you'll often encounter in the wild, so it's good exposure to various topics. But probably not worth much of your time.
And lastly, there is good history in here from people who know the space intimately. It's a good way to piece together the developments and learn the lexicon of deep learning so you can have intelligent conversation with experts.
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Reviewed in the United States on January 21, 2020
★★★★★ 5
The best DL/ML book I have ever seen!!
Format: Hardcover
Fantastic deep-learning book! The logic is very easy to follow, but the content is very thorough when it comes to explaining the theories behind it, making it perfect for beginners as well as math and CS students. The best DL/ML book I have ever seen!!
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Reviewed in the United States on November 30, 2025
★★★★★ 5
Comprehensive Look At An Incredibly Complex Topic
Format: Hardcover
Deep Learning is an advanced book with great explanations and details. There is a heavy math focus with the book's beginning chapters detailing the necessary linear algebra and probability that one will need to understand deep learning. I liked that the author's chose to cover only the parts of these subjects which are relevant to deep learning.
There are many interesting philosophical sections in the book as well. Just about when I was feeling overwhelmed with the complexity of the mathematics the authors take a step back and cover the foundations of deep learning such as borrowing concepts from human learning. There was an interesting dicussion about the early studies done on the vision of cat's and monkey's in the 1970s.
The text covers the entire history of deep learning and the bibliography is hundreds of sources. It is clear this is the most comprehensive text available about deep learning. For anybody interested in this topic this book is a mandatory read.
There are sections about machine learning as well, which makes sense because deep learning is a subset of machine learning. These sections focused on the machine learning concepts which are most relevant to deep learning.
The book was well organized and divided into three parts which cover mathematics related to deep learning, typical deep learning techniques, and then more experiment learning techniques. Often the author's state when a technique works well or when it does not, and which types of data works best for the technique.
Just a warning, the math in this book is highly complex. It requires a lot of work to go through this book, but the effort will be well rewarded.
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Reviewed in the United States on March 15, 2017
★★★★★ 4
Too Dry.
Format: Hardcover
This was a required textbook for my class in college. I think it was too dry.
The book titled Deep Learning: From Curiosity To Mastery is much more approachable.
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Reviewed in the United States on May 22, 2026