1/64 2.4G RC Mini Alloy Forklift With Trailer DIY Stickers
SPECIFICATIONS
Brand Name: NONE
CE: Certificate
Certification: CE
Choice: yes
Control Channels: 4 channels
Controller Battery: CR2032 3V button batteries(Included)
Controller Mode: MODE2
Features: Remote Control
Flight Time: 20-25mins
High-concerned chemical: None
Is Batteries Included: Yes
Is Electric: Lithium battery
Material: Plastic
Model Number: rc mini truck
Motor: Brushless Motor
Origin: Mainland China
Power Source: Electric
Recommend Age: 14+y,6-12Y
Remote Distance: About 15M
Scale: 1:64
State of Assembly: Ready-to-Go
Type: Truck
SPECIFICATION:
Name: 1:64 Mini Remote control alloy
Color: Yellow/green
Frequency: 2.4G
Applicable age: 6+
Materials: Plastic
Body Battery: 3.7V 200mah Polymer lithium battery(Included)
Remote control battery: CR20323V button batteries(Included)
Product size: 23*4*6.5CM
Remote control distance: About 15M
Playing time: About 20-25min
Charging time: About 30-40M
Speed: 5km/h
Function: Forward, backward, left turn, right turn, lights, music, speakers, up, down, speed adjustment, automatic demonstration,2.4GHz, supports mobile APP connection, alloy materials, accessory replacement.
FEATURES:
1. 2.4G remote control, no interference when use simultaneously with multiple units.
2. Mini simulation model, alloy body and forks, with lights and sound effects.
3. Supports APP mobile phone connection for remote control, with multiple gameplay options.
4. Forward, backward, left turn, right turn, light, music, horn, up, down, three-speed adjustment, automatic demonstration.
5. DIY stickers, freely decorate the car body.
PACKAGE LIST :
Car*1, Rear drag board*1, Instructions*1, Stickers*1, Charging cable*1, Fork*2, Carrier board* 1, Remote control*1, Crane accessories*1, Accessory bag*1,
Note:
1. The color of the item may be slightly different from the pictures shown on website caused by many factors such as brightness of your monitor and light brightness. Please refer to the actual product received.
2. Please allow slight manual measurement deviation for the data.


















