1. Introduction
Urban public transport plays a very important role in society, as it is the current means of transport serving a significant number of people every day. The sustainable tendency of urban mobility is to transport as many people daily as possible, with ecological, nonpolluting means of transport, which will have a direct effect not only on the reduction of the greenhouse gases (GHG), but also on the reduction of the environmental noise, traffic congestion, and the infrastructure vibration due to the vehicles equipped with internal combustion engines (ICE).
Most electric vehicles adopt AC motors due to their higher reliability and longer service life. Various electric motors and batteries used in electric vehicles are still subject to research, and innovative strategies are explored to compete with thermal-engine technology [
1].
Due to the tendency of the big cities agglomeration, there is a need to increase the number of buses in the public transport fleets, and if the bus fleet is not renewed with environmentally friendly, nonpolluting means of public transport, it will result an increase of the environmental pollution (chemical and acoustic) that would affect the health of the population. Also, by renewing the bus fleet park of the public transport companies, the aim is to encourage the use of the environmentally friendly, nonpolluting means of transport, to the detriment of using personal cars in urban traffic.
In [
2], Grijalva et al. noted that a bus used at the nominal occupancy level could replace up to 40 personal cars from urban traffic.
Regarding the problems mentioned above, the main solution for eliminating them is to replace the classic buses equipped with ICE with silent and nonpolluting electric buses.
However, this solution has two major drawbacks: the high purchase price of an electric bus (which can be double compared to a classic bus with the same capacity [
3], but which can be compensated by accessing European non-reimbursable funds [
4]), respectively the autonomy of the electric bus, which depends on the capacity of the batteries that equip this bus and on the charging strategy (fast charging between buses route, respectively slow charging overnight) [
5]. Because the batteries are the most expensive elements of an electric bus [
6,
7] and also have a considerable mass (between 1500 and 3000 kg) [
8,
9], the energy store in them must to be used to the maximum. The energy consumption for the electric bus varies according to a large number of parameters (the technology used in the construction of the electric bus, the experience of the driver, the traffic conditions, atmospheric conditions, the altitude profile of the route, the degree of the boarded passengers, etc.) between 1.0 and 3.5 kWh/km [
10,
11,
12,
13,
14].
The batteries of the electric buses are recyclable, and their major advantage is the operational costs with electricity that is much cheaper than conventional fuels [
3], respectively the maintenance costs that practically do not exist for a period of up to 10 years [
15]. The most important feature of a battery pack is to store a maximum amount of energy in a volume and at a minimum mass, in order to ensure the maximum autonomy [
16].
In [
17], Demircali et al. studied a virtual model for a battery of an electric vehicle, directly dependent on the ambient temperature, showing that, with the increase or decrease of this temperature, the energy stored in the battery is changed.
The energy consumption for the electric vehicles is influenced by the atmospheric conditions, not only from the point of view of the direct influence on the storage capacity of the batteries, but also from the point of view of the increase of the energy consumption due to the supply of the auxiliary systems (heating, ventilation, and air-conditioning in the vehicle), as demonstrated by Iora et al., in [
18].
In [
5], Vepsäläinen et al. showed that the optimal energy consumption of an electric bus takes place at an ambient temperature of 20 °C. However, the studies of Qian et al. [
19] showed that ambient temperature plays an important role in the battery life of an electric vehicle and, therefore, implicitly on the energy storage capacity. Thus, the increase or decrease in ambient temperature above certain thresholds lead to the more frequent use of cooling or heating, resulting in premature aging of the battery and the reduction of its storage capacity.
In different climatic zones, the ambient temperature can directly influence the efficiency of an electric vehicle, having the effect of increasing the energy consumption due to the use of air-conditioning systems for cooling or heating [
10,
20,
21,
22,
23,
24,
25]. In [
24], Yuksel et al. showed, by analyzing the energy consumption according to the ambient temperature during more than 7000 trips in six regions of the US, that the energy consumption for extreme values of the ambient temperature can be doubled (–30 °C to +40 °C), but it is kept at optimum values for a thermal regime between +17 and +27 °C.
Zhu et al. [
26] showed that, under extreme temperature conditions (–30 °C to +40 °C), the energy efficiency of the electric bus batteries is low and, at the same time, the degradation of the battery characteristics is accelerated. These authors demonstrate the importance of the thermal management of the batteries which, regardless of the atmospheric conditions, must ensure an optimum temperature on the surface of the batteries around +30 °C.
The studies conducted by Jardin et al. in [
27] showed that the optimum operating temperature for an electric bus based on energy consumption (kWh/km) is in the range between +20 and +25 °C, the maximum consumption being at low ambient temperatures.
The main objective of this work is to highlight the energy consumption and, respectively, the energy recovered for a fleet of 22 electric buses, Solaris Urbino 12e type, which operate on eight urban lines, on a route about 100 km from the city Cluj-Napoca, Romania. The consumption was monitored for 12 consecutive months (July 2018–June 2019). The temperate climate that characterizes most of the cities located in the continental area of Europe implies the existence of four seasons with extreme differences of environment temperatures (from –30 °C in the winter months and up to +40 °C in the summer months) [
28,
29,
30], differences that can have a significant impact on the electric buses autonomy.
3. Results
As the costs associated with the integration into the urban transport system of the electric buses are high, it is necessary to carry out studies and research in order to provide the best solution in relation to their optimal use, taking into account the particularities imposed by the zoning characteristics (length and the gradient of routes, the flow of the transported passengers, the loading infrastructure, the volume of traffic, the characteristics of the environment, etc.).
The study of the energy performances for the 22 electric buses during the monitored period (July 2018–June 2019) highlighted their behavior at different values of the climatic parameters (temperature, humidity, atmospheric pressure, and air density).
The climatic parameters were monitored during a calendar year and give a clear picture regarding the atmospheric conditions and their influence on the energy consumption, respectively, on the energy recovery during the operation of the electric buses.
The parameters resulting from the behavior of the driver are invariable, difficult to estimate and impossible to generalize because they are psychological factors specific to each individual. However, taking into account the data on variations in atmospheric pressure and air density, there is the possibility to correlate human behavior with these variations, so that in the situation of increasing these values, the behavior of drivers becomes more active, and in the situation of decreasing these values, behavior becomes more passive.
From the results captured in
Table 5 and in
Figure 13, the average annual values of the climatic parameters can be obtained, as follows: the average annual temperature, 11.6916 °C; the average annual humidity, 75.3083%; the average annual atmospheric pressure, 726.6333 Torr; average annual energy consumption of 1.3716 kWh/km; average annual energy recovery, of 0.4016 kWh/km. Taking these into account, in
Figure 14,
Figure 15,
Figure 16,
Figure 17 and
Figure 18 the variations of the respective parameters are presented, as monthly average values obtained, compared with their annual average values.
A summary of the obtained results, as the interdependence between them and the influence parameters on them, is captured in
Figure 19. Thus, for each considered month from the monitored period (July 2018–June 2019), the influence of the atmospheric conditions on the energy efficiency of the studied electric buses was highlighted. Also, for each considered month, the reciprocal link between temperature, humidity, atmospheric pressure, and air density is captured in
Figure 19. Thus, it was found that with the increase of the temperature, there is a reduction in air density, a slight decrease in atmospheric pressure, and the recorded humidity showed a reduce tendency. The recorded values of the humidity show that, with its increase, the air density increases, and the atmospheric pressure is reduced. It also notes that the increase in pressure indicates an increase in air density.
Regarding the energy consumption of the electric buses, it can be seen that it increases with decreasing the temperature and the atmospheric pressure, but the same tendency exists in the situation of increasing the air humidity and the air density (
Table 6 and
Figure 19). The energy recovered by the regenerative braking of the electric buses increases with the increase of the temperature and decreases with the increase of the air humidity, air density, and atmospheric pressure. Also, it can be seen that energy recovery largely compensates for the energy consumption of the electric buses.
4. Discussion
In the summer months (July 2018, August 2018, and June 2019), it resulted in high energy consumption compared to the average monthly values, due to the use of the air-conditioning system, when the ambient temperature exceeded 30 °C. This temperature threshold was imposed from the construction of the electric buses and results in the automatic operation of the air-conditioning until the ambient temperature in the passenger compartment drops below 25 °C. Regarding the recovered energy, an increase of it with the increase of the ambient temperature was noticed, under the conditions of maintaining low values of the atmospheric humidity, which facilitates the braking capacities of the electric buses on a dry road, respectively the increase of the electrical resistance of the braking system, preventing the energy losses through braking rheostats. In the summer months, characterized by the average monthly temperature values (see
Table 5) higher than the annual average, with 79.61% in July 2018, 79.61% in August 2018, and 98.43% in June 2019 (see
Figure 14), the atmospheric humidity is higher than the annual average by 0.25% in July 2018, lower by 9.57% in August 2018, and with 9.31% in June 2019 (see
Figure 15), and the atmospheric pressure is lower than the annual average by 0.39% in July 2018, higher by 0.09% in August 2018, and with 0.04% in June 2019 (see
Figure 16), resulting in lower energy consumption compared to the average annual consumption, by 17.62% in July 2018, 15.43% in August 2018, and 3.04% in June 2019 (see
Figure 17), and a higher amount of energy recovered compared to its annual average, with 7.05% in July 2018, 21.99% in June 2019, and lower by 0.41% in August 2018 (see
Figure 18).
From the recorded results, it can be seen that the autumn months (September 2018 and October 2018) are the months with low energy consumption, mainly due to the thermal conditions, with values of temperature of approx. 20 °C, but also with low values of the atmospheric humidity, being generally dry weather, which facilitates the movement of the electric buses with a minimum of energy consumed and a maximum recovered energy. During these months, the monthly average temperatures (see
Table 5) were higher than the annual average, with 59.09% in September 2018 and with 14.61% in October 2018 (see
Figure 14), with lower atmospheric humidity compared to that annual average with 11.69% in September 2018 and with 7.58% in October 2018 (see
Figure 15), and the atmospheric pressure higher than the annual average, with 0.28% in September 2018 and with 0.33% in October 2018 (see
Figure 16), resulted in a lower energy consumption than the average annual consumption, with 21.99% in September 2018 and with 5.43% in October 2018 (see
Figure 17), and a higher amount of energy recovered compared to its annual average, with 4.56% in September 2018 and with 7.05% in October 2018 (see
Figure 18).
Since November 2018, the cold season has started, which, due to the decrease of the ambient temperature, especially in the time periods from the beginning of the work program (from 5:00 a.m. to 8:00 a.m.), respectively in the periods after the end of the work program (from 8:00 p.m. to 11:00 p.m.), resulted in an accelerated increase of the average energy consumption. Due to the increase of the atmospheric humidity and the reduction of the grip due to the wet road, the value of the recovered energy decreased. November 2018 was characterized by monthly average values of the temperature lower than the annual average value with 57.23% (see
Figure 14), the atmospheric humidity higher than the annual average with 12.47% (see
Figure 15), and the atmospheric pressure compared to the annual average by 0.50% higher (see
Figure 16), resulted a higher energy consumption than the average annual consumption, by 5.71% (see
Figure 17), and a lower amount of recovered energy compared to its annual average, with 5.39% (see
Figure 18).
The winter months (December 2018 and January 2019) were the months with the lowest temperatures in the entire monitored period. In addition to the negative temperatures of the day, the start of the working program for the electric buses took place below the freezing threshold. Electric buses, which are connected overnight to the external slow-charging stations, and the batteries are heated by the thermal management system, consume, on the cold winter days (with temperatures below −10 °C) up to 10% of the energy from the batteries, for heating the interior passenger compartment, only in the interval of preparation for the buses’ departure on the route. Thus, combined with the increased of the daily consumption and the wet road conditions, it is reached that, during the cold season, the consumption increase by 2 to 2.5 times compared to the periods with the lowest values of consumption, and the energy values recovered will near zero. During these months, the monthly average temperatures (see
Table 5) were lower than the annual average by 101.71% in December 2018 and by 106.84% in January 2019 (see
Figure 14), the humidity was higher than the annual average with 27.34% in December 2018 and with 25.75% in January 2019 (see
Figure 15), and the atmospheric pressure was higher than the annual average, with 0.28% in December 2018 and lower, with 0.71% in January 2019 (see
Figure 16). The result was a higher energy consumption than the average annual consumption, with 29.77% in December 2018 and 38.52% in January 2019 (see
Figure 17), and a reduced amount of energy recovery compared to its annual average, by 27.80% in December 2018 and by 25.31% in January 2019 (see
Figure 18).
The transition from extremely low winter temperatures to thermal relaxation took place in February 2019, which started with low temperatures, especially in the early morning, but also with a slight increase in temperatures in the second half of the day, which have to lead to a reduction in energy consumption. Due to low values of the atmospheric humidity and the lack of precipitation, respectively, on a dry road, the amount of energy recovered during this period also increased. February 2019 was characterized by monthly average values of the temperature lower than the annual average value by 81.18% (see
Figure 14), the atmospheric humidity higher than the annual average by 6.76% (see
Figure 15), and the atmospheric pressure compared to the annual average higher with 0.44% (see
Figure 16). In February it resulted in higher energy consumption than the average annual consumption, with 16.65% (see
Figure 17), and a reduced of the energy recovery compared to its annual average, with 25.31% (see
Figure 18).
The spring months (March 2019 and April 2019) began with accelerated warming of the weather, with the reduction of the atmospheric humidity, environmental aspects that led to the gradual reduction of the energy consumption to normal values and to the increased of the energy recovery. Even though, during the two months, the mornings were colder, with temperatures around 0 °C, the thermal regime did not influence the electric bus batteries when the buses started on the route. During these months, the monthly average temperatures (see
Table 5) were lower than the annual average by 29.86% in March 2019 and higher by 0.93% in April 2019 (see
Figure 14), with lower atmospheric humidity compared to the annual average, with 17.41% in March 2019 and with 20.99% in April 2019 (see
Figure 15), and the atmospheric pressure was lower than the annual average, with 0.06% in March 2019 and with 0.20% in April 2019 (see
Figure 16), and it resulted in lower energy consumption compared to the average annual consumption, with 5.22% in each of the two months (see
Figure 17), and a reduced amount of energy compared to its annual average by 0.41% in March 2019 and by 19.50% higher in April 2019 (see
Figure 18).
The transition to the hot season at summer temperatures began in May 2019, a month characterized by positive thermal values throughout the operating range of the electric buses, respectively by the average values of the atmospheric humidity. These climatic factors allowed us to achieve average energy consumption within the normal limits specified by the manufacturer, cumulating with maximum energy recovery for the entire monitored interval. May 2019 was characterized by monthly average values of the temperature higher than the annual average value, with 29.15% (see
Figure 14), the atmospheric humidity higher than the annual average by 3.97% (see
Figure 15), and the atmospheric pressure lower than the annual average by 0.61% (see
Figure 16). In May, it resulted in lower energy consumption than the average annual consumption, by 6.68% (see
Figure 17), and an amount of recovered energy higher than its annual average, with 24.48% (see
Figure 18).
5. Conclusions
The energy efficiency of the electric buses was evaluated for 12 consecutive months (July 2018–June 2019), based on the weather conditions in Cluj-Napoca city, Romania, conditions that are specific to the vast majority of continental Europe, taking into account other area features, such as the loading infrastructure, traffic conditions, altitude profile of the traveled routes, the degree of loading with passengers, and the traffic management.
Based on our findings, the following conclusions can be drawn:
The climatic parameters influence the consumption and energy recovery for the electric buses;
The energy consumption of the electric buses increases with the decreasing of the temperature and the atmospheric pressure, but the same tendency exists even if the humidity and density of the air increase;
The energy recovered by the regenerative braking of the electric buses increases with the increase of the temperature and decreases with the increase of the air humidity, its density, and the atmospheric pressure;
Energy recovery largely compensates the energy consumption of the electric buses;
The variations of the monitored parameters, obtained as monthly average values, compared with their annual average values, highlight the interdependence of these quantities;
Average energy consumption, within the normal limits specified by the manufacturer and maximum energy recoveries, was obtained on the transition to the warm season;
The energy consumption of the electric buses increases when the buses accelerate or when the buses climb the ramps, and it decreases when the buses decelerate or descend from the ramp.
The authors intend to develop various models to describe other influences on the energy balance of the electric buses, to use them in their modeling, simulation, and exploitation. In addition, based on the collected experimental data and on the technical characteristics of the real model of the electric buses, the authors have already highlighted, with promising results, the influence of the atmospheric conditions on their energy balance, taking into account the interdependence of the climatic parameters (ambient temperature, atmospheric humidity, air pressure, and air density).