Standard driving cycles are usually used to compare vehicles from distinct regions, and local driving cycles reproduce more realistic conditions in specific regions. In this article, we employed a simple methodology for developing local driving cycles and subsequently performed a kinematic and energy analysis. As an application, we employed the methodology for cars and motorcycles in Recife, Brazil. The speed profile was collected using a smartphone (1 Hz) validated against a high precision global positioning system (10 Hz), presenting a mean absolute error of 3 km/h. The driving cycles were thus developed using the micro-trip method. The kinematic analysis indicated that motorcycles had a higher average speed and acceleration (32.5 km/h, 0.84 m/s2) than cars (22.6 km/h, 0.55 m/s2). As a result of the energy analysis, it was found that inertia is responsible for most of the fuel consumption for both cars (59%) and motorcycles (41%), but for motorcycles the aerodynamic drag is also relevant (36%). With regards to fuel consumption, it was found that the standard driving cycle used in Brazil (FTP-75; 2.47 MJ/km for cars and 0.84 MJ/km for motorcycles) adequately represents the driving profile for cars (2.46 MJ/km), and to a lesser extent motorcycles (0.91 MJ/km) in off-peak conditions. Finally, we evaluated the influence of the vehicle category on energy consumption, obtaining a maximum difference of 38% between a 2.0 L sports utility vehicle and a 1.0 L hatchback.

Local driving cycles (LDCs) capture local traffic characteristics, while standard driving cycles (SDCs) compare vehicles in distinct regions. There is a plethora of LDCs, raising the question as to how distinct they are. To quantify it, we first organized a collection of 77 LDCs. From the speed—time images, it was possible to extract numerical vectors of 40 cycles in a standardized way. Comparing the LDCs developed for cars, we found that their parameters fluctuate significantly: the average speed varies from 14.7 to 44.7 km/h, and the fuel economy varies from 10.8 to 20.5 km/L. Comparing the LDCs with FTP-75 cycle, the difference in speed is 7 km/h, and in fuel economy is 1.5 km/L. For WLTC, the difference is 19.4 km/h and 3 km/L, respectively. Thus, given the deviations found between the analyzed LDCs, and between LDCs and SDCs, the numerical results reinforce the relevance of using LDCs for each region.

This study presents and discusses the evolution of the Brazilian fleet. It is studied the engine and vehicle characteristics (price, registration, engine capacity, maximum power, weight, length, and vehicle segment) from 2003 to 2018, and CO2 emission, urban and road fuel consumption from 2013 to 2018, highlighting changes and its possible reasons. In general, Brazilian cars became cheaper, heavier, and more powerful. Despite the increase in weight and power, the CO2 emission were always inside the government targets. Additionally, it is compared the Brazilian and European average car, and Brazilian cars were cheaper, lighter, shorter, less powerful, and less economical.

This study aimed to determine whether a single local driving cycle (LDC) can effectively represent different cities in the same country, in both urban and highway routes, and for cars and motorcycles. To achieve this, experienced drivers drove different monitored vehicles (five cars and three motorcycles) on seven selected routes in two Brazilian states (Pernambuco and São Paulo State), collecting 170 h of speed data in urban and highway routes during peak and off-peak hours. Using the micro-trip and Markov chain methods, LDCs were then developed based on the collected real-world data. The kinematic and energy parameters of different route groupings were compared, revealing that two LDCs, one for cars and one for motorcycles, could be used to represent all urban routes. However, each highway route required a unique LDC. When compared with standard driving cycles adopted in Brazil, the created LDCs presented a coefficient of variation of 13%–46% in kinematic characteristic parameters, highlighting the need for developing LDCs to better represent Brazilian traffic.

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