- Science & Tech
Pune based carmaker Force Motors has introduced the 2017 edition of the Force Gurkha EOV (Extreme Off-road Vehicle) in the country with prices starting at Rs 8.38 lakh (ex-showroom, Delhi).
Available in 3-door Xplorer and 5-door Xpedition variants, the updated Gurkha gets a much-needed update with BSIV compliance in addition to a host of changes.
As a result, the off-roader will now be eligible to be sold in metro cities as well, which should help with its sales numbers.
The Force Gurkha is the automaker’s shining star in its list of passenger vehicles and is known for the highly capable off-roading skills. For the 2017 edition, Force has made changes to the SUV which makes it look like a replica of the Mercedes-Benz G-Wagon.
The off-roader can be ordered in both soft-top and hardtop versions, while you get sturdy bits like a steel bumper with foglamps as well as a factory fitted snorkel intake for better water wading capabilities.
The interior on the 2017 Force Gurkha has also seen a revision with new four-spoke steering wheel, redesigned floor console with new storage spaces and a new gear knob. You also get a manual air-con unit on the off-roader, albeit only on the hardtop version.
There have been structural changes as well, with the Gurkha riding on new C-in-C chassis frame put together using robotic welding, which helps in improved structural integrity.
Under the hood, power continues to come from the Mercedes OM 616 sourced 2.6 litre inter-cooled, direct injection, turbocharged diesel engine that is now BSIV compliant.
The oil burner is tuned to produce 84 bhp at 3200 rpm and 230 Nm of peak torque and comes paired to the G-28 5-speed all-synchromesh manual transmission.
Force Motors is offering 18 months and unlimited kilometre warranty on the 2017 Gurkha. The off-roader is one of the more capable models in the sub Rs 10 lakh space and with the model being more compatible, it also now poses as a direct threat to the Mahindra Thar.
However, the company needs to ramp up its sales and service network to make the model more attainable.