CC BY
25
https://doi.org/10.21122/2227-1031-7448-2019-18-6-504-508 UDC 656
The Analysis of Available Data on Energy Efficiency
of Electric Vehicles to be Used for Eco-Driving Project Development
M. Maljkovic1), D. Stamenkovic1), I. Blagojevic4, V. Popovic1
^University of Belgrade (Belgrade, Republic of Serbia)
© Белорусский национальный технический университет, 2019 Belarusian National Technical University, 2019
Abstract. The goal of this paper is to analyse the collected data on energy efficiency of electric vehicles from researches done by other authors and also to summarise all the factors affecting it. The majority of data available are obtained through simulations - therefore the emphasis in this paper will be placed on experimentally acquired data. The results of the analysis will be used for the planned e-bus eco-driving project for the purpose of Belgrade's public transportation system. Currently there are only 5 (ultracapacitor type) e-buses operating in Belgrade city public transport, which makes only 0.2 % of all vehicles in rolling stock (making 16 % together with other electric-powered vehicles - trams and trolleybuses), but there are plans to acquire new 80 electric buses. With the rise of the number of electric vehicles, appropriate training of drivers is gaining more and more importance, and the results of the presented analysis make the basis for such training. This will hopefully increase the range of the buses used and help save the energy spent by public transportation, thus giving a little contribution to global fight for cleaner planet.
Keywords: electric vehicles, energy efficiency, energy consumption, eco-driving, public transportation
For citation: Maljkovic M., Stamenkovic D., Blagojevic I., Popovic V. (2019) The Analysis of Available Data on Energy Efficiency of Electric Vehicles to be Used for Eco-Driving Project Development. Science and Technique. 18 (6), 504-508. https://doi.org/10.21122/2227-1031-7448-2019-18-6-504-508
Анализ имеющихся данных по энергоэффективности электромобилей,
которые будут использоваться
для разработки проекта экологического вождения
М. Малькович1), Д. Стаменкович1), И. Благоевич1), В. Попович4
^Белградский университет (Белград, Республика Сербия)
Реферат. Целью работы является анализ собранных ранее разными исследователями данных об энергоэффективности электромобилей, а также обобщение всех факторов, влияющих на нее. Большая часть из них получена с помощью моделирования, поэтому особое внимание в этой статье уделяется экспериментально установленным характеристикам. Результаты анализа будут использованы в рамках запланированного проекта по применению экологичного электробуса в системе общественного транспорта Белграда, где в настоящее время функционируют только пять электробусов (ультраконденсаторного типа), что составляет всего 0,2 % от числа всех транспортных средств подвижного состава (16 % вместе с другими электромобилями - трамваями и троллейбусами), но планируется приобрести 80 новых электробусов. С ростом количества электромобилей все большее значение приобретает соответствующая подготовка водителей, и результаты представленного анализа служат основой такой подготовки. Данный подход позволит расширить ассортимент используемых автобусов и сэкономить энергию, затрачиваемую общественным транспортом, что внесет определенный вклад в глобальную борьбу за чистую планету.
Ключевые слова: электромобиль, энергоэффективность, потребление энергии, эковождение, общественный транспорт
Для цитирования: Анализ имеющихся данных по энергоэффективности электромобилей, которые будут использоваться для разработки проекта экологического вождения / М. Малькович [и др.] // Наука и техника. 2019. Т. 18, № 6. С. 504-508. https://doi.org/10.21122/2227-1031-2019-18-6-504-508
Адрес для переписки
Благоевич Иван
Белградский университет
ул. Кральице Марие, 16,
11120, Белград 35, Республика Сербия
Тел.: +381 11 337-02-66
iblagojevic@mas.bg.ac.rs
Address for correspondence
Blagojevic Ivan
University of Belgrade
16 Kraljice Marije str.,
11120, Belgrade 35, Republic of Serbia
Tel.: +381 11 337-02-66
iblagojevic@mas.bg.ac.rs
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Introduction
By looking at Tab. 1, it can be seen that currently there are only 5 electric (ultracapacitor type) buses operating in Belgrade public transportation system, with 80 new e-buses planned. It is expected that this trend will continue [1], so it is very important to take all the advantages of electric buses usage. In order to make it possible, a new eco-driving project is planned. As a preparation for this project, a research on energy efficiency of electric buses needs to be conducted. There are many factors affecting it [2], and this paper will try to summarise them.
Table 1
Belgrade public transportation system rolling stock
The analysis
Two hundred electric vehicles (3 models made in the same factory and sharing the same platform) were driven by 741 drivers travelling more than two million kilometres during two years to explore the effects of weather conditions, travel distance and vehicle speed on the energy consumption [3]. The results show that winter period increases the consumption by 34 % compared to summer period, reducing the autonomy by 25 %. The outside temperature of 14 °C was found to be the most suitable.
The effects of ambient temperature and vehicle auxiliary loads (air conditioning, heating and ventilation) were investigated in another study [4], collecting data from 68 electric vehicles in Japan for one year period, showing that the temperature range of 21.8 to 25.2 °C is most favourable to energy efficiency of the vehicle. Another important conclusion is that about 10 % of energy can be saved by minimising unreasonable auxiliary loads.
Technical Research Centre of Finland (VTT) conducted a research in their laboratory using different driving cycles (Tab. 2) [5].
The research showed that 23/-20 °C temperature drop, with cabin heater turned off, will shorten the range by 20 % (30 % in worst case).
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The results for each cycle are shown in Tab. 3. The use of 4.5 kW cabin heater can shorten the range for more than 50 % in urban driving cycles and by approximately 20 % on open road (Tab. 4).
Table 2
The main parameters of driving cycles used
Cycle Distance, km Fverage speed, km/h Maximum speed, km/h Stops during cycle Run time, s
EURO 11.007 33.6 120 12 1180
ECE15 4.052 18.7 50 4 780
EUDC 6.955 62.6 120 0 400
Helsinki city 6.600 19.1 55 17 1360
Artemis urban 4.488 17.6 58 19 993
Road, FIN 24.800 81.3 120 1 1370
Artemis road, EV* 16.641 60.3 111 1 981
Artemis motorway, EV* 23.793 105.6 130 0 736
Table 3
Estimated range for each driving cycle
Estimated range Difference
Cycle +23 °С, -20 °С, -20 vs +23,
km km %
EURO 124 88 -29
Helsinki city 125 106 -15
Artemis urban 99 74 -26
Road, FIN 91 70 -23
Artemis road, EV* 113 90 -20
Artemis motorway, EV* 72 53 -26
Average, all cycles 100 79 -21
Table 4
The impact of cabin heater use for each driving cycle
At -20 °C, 4.5 kW heater cycle Heater energy, kW-h Total energy, kW-h Estimated range, km Relative impast, %
EURO 0.134 0.334 53 -40
Helsinki city 0.236 0.402 44 -59
Artemis urban 0.256 0.494 36 -52
Road, FIN 0.055 0.307 57 -18
Artemis road, EV* 0.075 0.270 65 -28
Artemis motorway, EV* 0.043 0.371 47 -11
One research showed that the most economical average vehicle speed is between 45 and 56 km/h (Fig. 1), and that electric vehicles are more energy efficient for longer trips [3].
In another research, converted electric vehicle was driven for five months in real-world conditions [6]. The results showed that electric vehicles are more efficient in urban driving conditions than
Buses 2000
Trolleybuses 119
Electric buses 5 (80 new planned)
Trams 247
Total 2371 (2451)
on highway, owing it to lower speeds and more frequent recuperation. However, this advantage cannot be always used, because the regenerative braking is not in function when battery is in high state of charge or when battery temperature is high [7]. By comparing several electric vehicles in 16 different driving cycles [8], it was shown that in urban conditions, a vehicle with a higher weight can benefit more from regenerative braking.
Average speed, km/h
Fig. 1. The effect of average vehicle speed on the energy consumption
The results of another research [9] show that speed lower than 40 km/h and ambient temperature about 20 °C are optimal in terms of energy efficiency of electric vehicles. The researches founded that in some specific driving conditions auxiliary systems can reduce vehicle autonomy by 50 %. They also found that about 1 % of energy is consumed by light and signalling devices.
Tab. 5 shows the impact of auxiliary systems on energy efficiency of electric vehicles [10] obtained by the Idaho National Laboratory. Again, cabin heater is identified as most influential, leaving air conditioning device closely behind.
Table 5
Impact of auxiliary systems on electric vehicle energy consumption
The research conducted in laboratory conditions on 3 different electric vehicles tested in few driving cycles in accordance with SAE J1634 showed that autonomy at -7 °C is reduced by approximately 20 % in comparison with 20 °C, with cabin heater reducing it for additional 25 %. At -20 °C the autonomy is reduced by 60 % with cabin heater turned on [11].
A project [12] sponsored by the French Environment and Energy Management Agency and conducted with the help of few vehicle manufacturers also gave some conclusions on electric vehicle energy consumption influencing factors, based on simulation results, validated through certain driving cycles performed on chassis dynamometer. It is stated that auxiliary systems consume about 15-40 % at average speed of 20 km/h and 5-15 % at average speed of 60 km/h. Regenerative braking also has a great (positive) influence on energy consumption with efficiency of about 50 % at 20 km/h and about 30 % at 60 km/h. The study also showed that economical driver (0.38 m/s2 mean acceleration) can save approximately 40 % of energy at low speeds and 10 % at high speeds, compared to aggressive driver (1.03 m/s2 mean acceleration).
Researchers at the Aalto University performed simulations using several driving cycles (Tab. 6) in different operating conditions and for two different electric bus configurations, the first (EV1) with 77 kW-h battery and second (EV2) with 373 kW-h battery [13].
Table 6
Simulated driving cycles
Impact of equipment on EV performance
Accessory Range impact Comments
Air conditioning Up to 30 % Highly dependent on ambient temperature cabin temperature, and air volume
Heating Up to 35 % Highly dependent on ambient temperature and cabin temperature
Power steering
Power brakes
Defroster
Other lights, stereo, phone, power-assisted seats, windows, locks Up to 5 % Depending on use
BR E11 H550 H3 L51B MAN
Time, s 1740 1548 3384 902 4283 1089
Distance, km 10.9 10.2 28.7 10.3 16.1 3.3
Maximum speed, km/h 58.2 58.4 74.9 71.7 59.0 40.5
Average total speed, km/h 22.5 23.8 30.5 41.2 13.6 10.9
Average speed, km/h 30.1 27.9 36.0 48.4 20.2 17.1
Stops per, km 2.7 1.8 1.3 0.9 4.3 6.1
Aggressiveness, m/s2 0.235 0.152 0.206 0.195 0.281 0.306
Climbing gradient, m/km 0.00 5.75 6.80 0.00 7.27 0.00
Descending gradient, m/km 0.00 -5.83 -6.64 0.00 -7.26 0.00
Number of buses in a fleet 7 7 13 5 16 5
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Simulations were performed for vehicles loaded with half of passenger capacity and with constant power demand (6 kW) for auxiliary systems. Energy loss distribution for EV1 is shown in Fig. 2. It can be seen that main impacts on the energy consumption come from auxiliary systems, transmission and tyres. It can be seen that energy loss coming from rolling resistance is almost constant for all driving conditions. Aerodynamic drag also takes big part in energy loss at high speeds. Energy losses caused by auxiliary systems and in transmission are higher in driving cycles characterised by higher number of stops and lower average speed. The impact of vehicle weight due to passenger load is shown in Fig. 3. Again, this impact is more pronounced in driving cycles with lower average speed and higher number of stops. Fig. 4 shows the results of the same study and it shows that a higher aggressiveness increases the impact of passenger load on energy consumption in electric bus.
1,6
E
5 1.2 £ 1 ¡8
Eg
<0 -.4
LLI ~ -
0
H550
L51B
| Battery I Auxiliaries I Transmission ] Tyres ]Brake ] Aero
Fig. 2. EV1 energy loss distribution
H550 H3 Driving cycle
Fig. 3. Passenger load impact on energy consumption
70
E k
S
I?
<D
30
0.15
0.2
0.25
0.3
Aggressiveness, m/s2
Fig. 4. Passenger load and driving aggressiveness combined
CONCLUSIONS
1. There are steps that can be taken in design process [14] to make vehicles more efficient. However, the authors found three main factors, not relating to the vehicle itself, affecting the energy efficiency of electric vehicles - ambient temperature (as a trigger for auxiliary loads), traffic conditions (urban vs. extra-urban) and driving style.
2. There is a little that can be done to lower the effects of ambient temperature. The fact that electric vehicles are more economical in city driving conditions, primarily due to the regenerative braking, is advantageous for public transportation. The biggest contribution to more efficient usage of electric vehicles can be made by changing the driving style, which is the goal of the future eco-driving project that will hopefully taught the drivers to avoid high speeds, accelerate moderately, drive in anticipatory manner, minimise the auxiliary loads (within the limits), use regenerative braking more often and coast whenever possible [15].
3. Future research will incorporate the real-world tests to confirm the findings and make the best possible input for the mentioned eco-driving project.
ACKNOWLEDGEMENT
This paper is a result of project financed by the Serbian Ministry of Education, Science and Technological Development (TR 35045 - "Scientific-Technological Support to Enhancing the Safety of Special Road and Rail Vehicles", project leader - Prof. Dr Vladimir Po-povic).
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Received: 08.10.2019 Accepted: 29.11.2019 Published online: 06.12.2019
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