Tuner Tools provides automotive and tuning professionals with industry-exclusive and highly useful services that supplement the already powerful VCM Suite and series of OBDII interfaces. These services include our Neural Network Training and Tune Translation.
Conveniently access these tools on your Tuner Tools Portal, where your account information is shared with your main HP Tuners account.
TUNER TOOLS TOKENS
Tokens are the currency used to purchase any of these Tuner Tools services. These Tokens are exclusive to Tuner Tools and cannot be used anywhere else in the HP Tuners ecosystem.
Your Tuner Tools “My Account” page will show your current supply of Tokens and the full list of supported controllers and the cost of each service. Your account page is also where you can purchase additional Token bundles
Easily convert your binary files to .hpt files so you can edit and flash using our latest version of VCM Editor. Tune Translation performs binary conversions for many controller types.
Most controllers cost 50 tokens, but certain controllers are free of charge. The full list of supported controllers and costs can be found in the Tuner Tools Portal.
HOW TO GET STARTED WITH TUNE TRANSLATION
Navigate to Tuner Tools by HP Tuners.
Upload your .bin file.
Once Tune Translation completes the conversion, click the “Download” button for your .hpt file.
You will be prompted to confirm the consumption of 50 tokens (if applicable) from your account.
Open the downloaded .hpt file in the latest version of VCM Editor.
The Neural Network Trainer by HP Tuners provides industry-exclusive control over your vehicle’s neural networks so you can optimize your calibrations.
This new tool allows for the editing of your vehicle VE tables and simplifies the complex process of neural network training.
What are neural networks?
Neural networks are a set of advanced algorithms designed to recognize patterns. They "learn" by processing examples that include a known input and result. As modern vehicles become ever more complex, some manufacturers have begun to implement neural networks to optimize vehicle performance.
Neural Networks accept inputs like engine RPM, intake and exhaust camshaft positions, and more, perform several calculations, and produce an output that models estimated volumetric efficiency (VE). These vehicles have too many inputs to reasonably handle using traditional methods, which has led to the usage of neural networks.
HOW TO USE THE NEURAL NETWORK TRAINER
Read your vehicle’s current tune using VCM Editor. If eligible for Neural Network Training, the option will appear in the EDIT menu, open VE Neural network trainer.
In VCM Editor the network trainer box will appear, click create new file for training from your vehicle’s current tune and save the untrained file to your computer.
Upload your untrained file to the Neural Network Trainer found at Tuner Tools. Once it’s processed, download and save the result file. Upload the new result file into the network trainer in VCM editor, you’ll now have access to the VE tables.
Modify the VE tables as desired, save your current progress then export them for training. Navigate back to Tuner Tools to upload and train the newly modified exported file.
Download the trained result file once again, load it into the Neural network trainer in VCM Editor, and flash your vehicle with updated values.
Repeat training the files until the desired result is achieved.
Download a detailed step-by-step User Guide for Neural Network Trainer.
Note: 25 Tuner Tools Tokens will license your vehicle for one month of Neural Network training. During this month you can retrain as many times as required under the same license. Certain vehicles may require multiple iterations of Neural Network training to achieve desired results.
Note: Select 2010+ FCA and 2019+ GM vehicles are eligible for neural network training.
NEURAL NETWORK TRAINER FAQ
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How does the Neural Network Trainer work and why do I need it?
The neural networks in the FCA and GM vehicles take certain inputs like engine speed, cam angle, etc., run some calculations, and provide an estimated volumetric efficiency given those inputs. The parameters which define the neural network are called weights and biases. While the neural network can interpret those parameters and use them to run calculations, to a human, those numbers provide little to no meaning. The goal of the Neural Network Trainer is to allow tuners to modify the neural network in their vehicles using a method they are familiar with: VE Tables.
When a file is initially generated, the Neural Network Trainer will generate VE Tables for the provided neural network parameters. The tuner then modifies the initial VE tables as desired and uploads the new file for training. The Neural Network Trainer will find new parameters for the neural network which fit the provided VE tables as closely as possible. At that point, the new neural network parameters can be written to the vehicle and the tuner can test the changes.
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How to change the range of input and output parameters like RPM, PRatio, etc.?
For FCA vehicles: Open the “Engine > Airflow > Neural Network” tab. The “Training Values” section contains the allowed range for all the input and output variables of the neural network
For GM vehicles: Open the “Engine > Airflow > Speed Density” tab. “Input Layer > Min Range, HL” contains the minimum allowed range for the input variables. “Input Layer > Max Range, HL” contains the maximum allowed range for the input variables. The range for the output VE can be modified by changing the “Outer Layer > Min Range, HL” and the “Outer Layer > Max Range, HL” values.
Note: the input and output value ranges must be changed before creating the initial file in the Neural Network Trainer. If the values are changed after a file was created, it will be necessary to create a new file by clicking the “Create New File for Training from Tune” button.
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Do I really need to modify all 25 VE tables for FCA vehicles?
Depending on the desired accuracy, users may disable some of the VE tables for training. This can be done by unchecking the “Use Table for Training” checkbox in the Neural Network Trainer. For some vehicles like the Dodge Hellcat, only 5 tables need to be trained because the intake and exhaust camshafts are linked together. To view the possible combinations of intake and exhaust camshaft angles for your FCA vehicle, open the “Engine > Airflow > Variable Camshaft” tab and open the “Intake Camshaft, Desired Angle, Normal” and “Exhaust Camshaft, Desired Angle, Normal” tables. These tables will show what is the target intake and exhaust camshaft angle for each engine rpm and aircharge value.
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Why isn’t this tool part of VCM Suite?
Training a neural network is a very resource-intensive task. For the training process to run in a reasonable amount of time, we use high-performance servers that can train a neural network in under 2 minutes. This way tuners can continue modifying vehicles without having to buy an expensive computer.
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What VCM Scanner parameters represent the inputs to the Neural Network?
For FCA vehicles: RPM, Pressure Ratio, Intake Cam Angle, Exhaust Cam Angle
For GM vehicles: RPM, Cylinder Airmass, Intake Cam Angle from Open Position
Note: “Intake Cam Angle from Open Position” is only available in VCM Suite versions 4.9.389 and newer.
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How do I get fuel trims for a certain intake and exhaust camshaft angle using VCM Scanner?
Right-click on the Graph area in VCM Scanner and select Graphs Layout. Go to ST Fuel Trim or LT Fuel Trim depending on which one you want to use. In the “Filtering” section click on “New Variable” and select “Intake Cam Angle”. Depending on the vehicle, the variable might have a slightly different name.
Next set a range of values for which you would like to filter out the fuel trims. This is how the filtering function would look if we want to get the fuel trims between 104 and 106 degrees of intake cam angle: “[2172.161]>104 and [2172.161]<106”.
Next, add the Exhaust Cam Angle variable and add a similar condition for the desired exhaust cam angle range. More conditions can be added by using the “and” keyword between each condition.