SKU: 99410871644

Brembo 12-21 BMW 228i/228i xDrive/230i/230i xDrive/320i Brake Wear Sensor - Rear

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Description

Brembo 12-21 BMW 228i/228i xDrive/230i/230i xDrive/320i Brake Wear Sensor - RearBrembo Brake Pad Wear Sensors are designed to keep driver aware about the vehicles brake pads remaining life and when they are due for replacement. The electronic wear sensor monitors the brake pad thickness on your vehicle and sends a signal warning that your brake pads are at minimal thickness and need replacing. Made to OE specifications, your new Brembo brake pad wear sensors will perform exactly like the original wear sensors on your vehicle.

Brembo Brake Pad Wear Sensors are designed to keep driver aware about the vehicles brake pads remaining life and when they are due for replacement. The electronic wear sensor monitors the brake pad thickness on your vehicle and sends a signal/warning that your brake pads are at minimal thickness and need replacing. Made to OE specifications, your new Brembo brake pad wear sensors will perform exactly like the original wear sensors on your vehicle. Brembo strongly recommends replacing the wear sensors with every brake pad replacement.

  • High-quality wiring and connectors resist high heat and harsh weather conditions

This Part Fits:

Year Make Model Submodel
2014-2016 BMW 228i Base
2015-2016 BMW 228i xDrive Base
2017-2021 BMW 230i Base
2017-2021 BMW 230i xDrive Base
2013-2018 BMW 320i Base
2013-2018 BMW 320i xDrive Base
2014-2018 BMW 328d Base
2014-2018 BMW 328d xDrive Base
2012-2016 BMW 328i Base
2014-2016 BMW 328i GT xDrive Base
2013-2016 BMW 328i xDrive Base
2016,2018 BMW 330e Base
2017 BMW 330e iPerformance
2017-2018 BMW 330i Base
2017-2019 BMW 330i GT xDrive Base
2017-2019 BMW 330i xDrive Base
2012-2015 BMW 335i Base
2014-2016 BMW 335i GT xDrive Base
2013-2015 BMW 335i xDrive Base
2016-2018 BMW 340i Base
2017-2019 BMW 340i GT xDrive Base
2016-2018 BMW 340i xDrive Base
2014-2016 BMW 428i Base
2015-2016 BMW 428i Gran Coupe Base
2014-2016 BMW 428i xDrive Base
2015-2016 BMW 428i xDrive Gran Coupe Base
2017-2020 BMW 430i Base
2017-2020 BMW 430i Gran Coupe Base
2017-2020 BMW 430i xDrive Base
2017-2020 BMW 430i xDrive Gran Coupe Base
2014-2016 BMW 435i Base
2015-2016 BMW 435i Gran Coupe Base
2014-2016 BMW 435i xDrive Base
2015-2016 BMW 435i xDrive Gran Coupe Base
2017-2020 BMW 440i Base
2017-2020 BMW 440i Gran Coupe Base
2017-2020 BMW 440i xDrive Base
2017-2020 BMW 440i xDrive Gran Coupe Base
2013-2015 BMW ActiveHybrid 3 Base
2016-2018 BMW M2 Base
2019-2021 BMW M2 Competition
2020 BMW M2 CS
2014-2016 BMW M235i Base
2015-2016 BMW M235i xDrive Base
2017-2021 BMW M240i Base
2017-2020 BMW M240i xDrive Base
2015-2018 BMW M3 Base
2015-2020 BMW M4 Base
2019-2020 BMW M4 CS
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Exchange/Return Notes
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SKU: 99410871644

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4.3 ★★★★★
Based on 28 reviews
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Z
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Zay
Lowell, US
★★★★★ 5
Upside down (Great)
Format: Hardcover
Was extremely relatable and a blessing I gifted this book and want it back lol but I will be ordering again
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on October 23, 2024
R
Verified Purchase
Rory Derrick
Houston, US
★★★★★ 5
Good book
Format: Paperback
Still working through it but I have no complaints. I have a shelf of no starch books and have not been disappointed by any. Some, of course, are better than others but this is a good book.
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Reviewed in the United States on December 2, 2021
C
Verified Purchase
Cory P.
Lowell, US
★★★★★ 5
Dive into Algorithms is more like eating a Parfait than trying understand algorithms!
Format: Paperback
Seriously though great writing and explanation along with great history lessons. Also highly recommend for anyone working in the data science field.
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Reviewed in the United States on August 3, 2021
F
Verified Purchase
Frank Gonzalez
Draper, US
★★★★★ 3
Ok content, not great explanations (2.5 our of 5 stars)
Format: Paperback
I found the contents of this book to be simply ok: either too simple, or the more complicated algorithms and concepts would not be as carefully explained as they should have been. It is not a terrible book, but it feels as though the author did not go over many drafts/iterations of this work.
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Reviewed in the United States on April 7, 2024
I
Ira Laefsky
Charlottesville, US
★★★★★ 5
An Excellent Self-Discovery Approach to Learning Algorithms
Format: Paperback
I have an Ivy League Master's Degree in Computer Science although it was accomplished 35 years ago. Of course, I had to complete an ACM-type course in Algorithms and Data Structures on the undergraduate and graduate level and managed to by rote accomplish enough to satisfy these courses. But until seeing this great book I never had the feeling of gaining an understanding of the approach to learning and building algorithms and the extent to which it is an important component of all programs. By a journey of guided self-discovery the author shows, not only the necessity of algorithms and their canonical forms, but a path to understanding the construction of algorithms to accomplish common and not so common practical problems. These range from the simple to understand, e.g. implementing Russian Peasant Multiplication, to advanced and up to date topics like Machine Learning. The highest praise I can give this book is that as a journey of guided self-discovery it produces an understanding in the reader of the process of constructing and understanding these algorithms and their place in all programming.
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Reviewed in the United States on February 7, 2021

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