Toyota: Rebellion and Ginetta 'will be stronger than ever in China'
Toyota Gazoo Racing is heading into the 4 Hours of Shanghai as championship leaders after two dominant victories, but believes the non-hybrid opposition will be stronger than before in round three of the championship.
The two Toyotas both sit at 44 points each, with the #7 of Mike Conway, Kamui Kobayashi and Jose Maria Lopez leading after victory in Silverstone. The #8 of Brendon Hartley, Kazuki Nakajima and Brendon Hartley won at Fuji in October, and with both also scoring one second place finish, the two cars are tied for points.
The two Toyotas have been reigned in further by the Success Ballast rules, meaning that the pair of TS050 Hybrids will be slowed down to the tune of 2.7 seconds this weekend. As a result, the Japanese manufacturer believes the challenge from non-hybrid rivals Rebellion Racing and Team LNT Ginetta will be as big as it's ever been.
“I have good memories of racing in Shanghai from our victory there last year; I hope we can stand on the top step of the podium again this time as well," said #7's Mike Conway. "It should be a great battle with the sister car, but I'm sure the non-hybrid LMP1 cars will be stronger than ever in China. It will not be an easy race but we're ready for it and looking forward to the challenge.”
While the regulations have impacted Toyota's available amount of ERS power per lap, fuel flow and the size of the fuel restrictor, Rebellion and Ginetta have only been hit with weight increases. The #1 Rebellion R13-Gibson of Bruno Senna, Gustavo Menezes and Norman Nato has been hit the hardest, losing 0.89s thanks to a 37 kilogram weight increase.
“I'm expecting a tough race in Shanghai but we enjoy a challenge and will give it our best shot," added Kazuki Nakajima, who took victory in Fuji with the #8. "There will be no margin for error at all; we have to be perfect in order to compete considering the performance we expect from the non-hybrid cars. We will all be working very hard to get the car set-up right for the race and get the maximum performance from our energy allocation."