The challenge of fine-tuning in Chinese car models
Industry experts highlight a notable shortcoming in many Chinese vehicles: chassis tuning. A study drawing on the work of Yuri Uryukov, a researcher at the NTI Avtonet Center of Moscow Polytechnic University, describes the issue with clarity. The car may feel composed at everyday speeds, yet when compared with well-tuned European or Japanese crossovers the difference in ride quality becomes obvious. European and Japanese models often glide more smoothly and offer steadier handling. The emphasis on how a vehicle responds during rapid overtaking and when facing an unexpected obstacle underscores a skill gap in tuning among some Chinese brands, according to Uryukov.
There have been prior observations that price does not always mirror performance. For example, a new Chinese car can be priced around 3.3 million rubles, with general price trends showing an annual rise of about 11 percent. Different brands have experienced varied pricing moves. Geely posted a higher average price increase, while Chery also registered significant gains. Other brands like Changan showed more moderate price growth, and Exeed and Omoda saw smaller margins. By contrast, the average price for Haval models edged slightly downward in the same period.
In the used-car segment, values for Chinese brands have climbed sharply. By the end of 2023, the average price of a used model had risen to roughly 1.8 million rubles, signaling strong demand and limited supply in the secondary market.
Market observers pose a pressing question: when will the decline in car prices in Russia reach a bottom? The inquiry reflects ongoing shifts in consumer demand, production costs, and market regulation. While some sectors see price moderation, other categories continue to experience changes driven by global supply chains and local economic conditions. The discussion points to a market still recalibrating after years of rapid pricing moves, with buyers weighing value, reliability, and long-term ownership costs as they compare new versus used options. [Citation: NTI Avtonet Center, Moscow Polytech University]