A system for dynamic inductive power supply of electric vehicles on the road

Author(s):  
Johannes A. Russer ◽  
Marco Dionigi ◽  
Mauro Mongiardo ◽  
Franco Mastri ◽  
Alessandra Costanzo ◽  
...  
2021 ◽  
pp. 143-155
Author(s):  
Erik Wilhelm ◽  
Wilfried Hahn ◽  
Martin Kyburz

AbstractThis paper is written from the perspective of a Swiss OEM which has been active in the small electric vehicle (SEV) market since 1991 and has put over 22,000 SEVs on the road around the world. KYBURZ Switzerland AG identified several important niche markets for SEVs and today sells vehicles to improve the mobility of senior citizens (e.g. KYBURZ Plus), to increase the efficiency of postal and logistics companies (e.g., KYBURZ DXP), and to imbue drivers with passion for electric vehicles (e.g., KYBURZ eRod). Most KYBURZ vehicles are currently homologated in the category L2e, L6e, or L7e. The company has also developed a Fleet Management product which gives its customers detailed insights into the performance of their electric as well as conventionally powered vehicles. Anonymized datasets from this Fleet Management system will be drawn upon in this paper to examine questions regarding their application, i.e., environmental and economic aspects. The unique feature which the authors from KYBURZ bring with this paper is that all their investigations are performed with real data gained from the field experience. The primary focus of this paper is on last-mile mobility services for postal organizations which help to increase efficiency and meet sustainability goals.


Author(s):  
Funso Kehinde Ariyo ◽  
Oluwafemi Aworo ◽  
Michael Kuku

There have been growing concerns involving the penetration of Electric Vehicles (EVs) due to the time required by its battery to attain full charge. Interests in EVs had recently experienced a dramatic turn down due to mileage limitation on full battery charge amidst the cost of purchase, but most notably due to the absence of quick chargers that can keep the vehicle on the road within few minutes of arriving at the charging station. Researchers had proposed different charging schemes such as level II ac charging, dc charging, and in some cases, wireless charging schemes that later appear to be inefficient. The use of dynamic or simply road-way powered electric vehicles was also proposed in the literature. However, the proposed cycloconverter-based circuit was simulated in Simulink, and the results obtained proved that the rate of charge increased when compared to the conventional EV charging circuit. Also, the focus is on battery charging technology and battery modeling for application in an electric vehicle


2013 ◽  
Vol 718-720 ◽  
pp. 1435-1439
Author(s):  
Teng Teng Li ◽  
Kong Jian Qin ◽  
Jun Hua Gao ◽  
Feng Bin Wang

On the road, fuel meter and electric power meter were employed to measure fuel consumption and electricity consumption of two parallel hybrid electric vehicles (PHEVs); Corrected methods recommended by SAE J2711 and GB/T 19754 respectively were used to modify fuel consumption of two vehicles through electricity consumption; According to the result, how total quality and Air-Condition (AC) load affect fuel economy were analyzed. Test results showed that, When K was less than 1%, relative error from calculation results of fuel consumption per 100 km obtained by above two methods was within 0.7%; Compared with AC off condition, fuel consumption per 100 km of PHEVs under AC on condition increased by more than 42%, which caused bad fuel economy, the effect of fuel-saving was decreased by 10% or more accordingly.


Author(s):  
Je-Liang Liou ◽  
Pei-Ing Wu

This is the first study to provide a systematic monetary benefit matrix, including greenhouse gas (GHG) emissions reduction benefits and air pollution reduction health co-benefits, for a change in on-the-road transport to low-carbon types. The benefit transfer method is employed to estimate the social cost of carbon and the health co-benefits via impact pathway analysis in Taiwan. Specifically, the total emissions reduction benefits from changing all internal combustion vehicles to either hybrid electric vehicles, plug-in hybrid electric vehicles, or electric vehicles would generate an average of US$760 million from GHG emissions reduction and US$2,091 million from health co-benefits based on air pollution reduction, for a total benefit of US$2,851 million annually. For a change from combustion scooters to light- or heavy-duty electric scooters, the average GHG emissions reduction benefits would be US$96.02 million, and the health co-benefits from air pollution reduction would be US$1,008.83 million, for total benefits of US$1,104.85 million annually.


2021 ◽  
Vol 2 (1) ◽  
pp. 1-24
Author(s):  
Liuwang Kang ◽  
Ankur Sarker ◽  
Haiying Shen

As Electric Vehicles (EVs) become increasingly popular, their battery-related problems (e.g., short driving range and heavy battery weight) must be resolved as soon as possible. Velocity optimization of EVs to minimize energy consumption in driving is an effective alternative to handle these problems. However, previous velocity optimization methods assume that vehicles will pass through traffic lights immediately at green traffic signals. Actually, a vehicle may still experience a delay to pass a green traffic light due to a vehicle waiting queue in front of the traffic light. Also, as velocity optimization is for individual vehicles, previous methods cannot avoid rear-end collisions. That is, a vehicle following its optimal velocity profile may experience rear-end collisions with its frontal vehicle on the road. In this article, for the first time, we propose a velocity optimization system that enables EVs to immediately pass green traffic lights without delay and to avoid rear-end collisions to ensure driving safety when EVs follow optimal velocity profiles on the road. We collected real driving data on road sections of US-25 highway (with two driving lanes in each direction and relatively low traffic volume) to conduct extensive trace-driven simulation studies. Results show that our velocity optimization system reduces energy consumption by up to 17.5% compared with real driving patterns without increasing trip time. Also, it helps EVs to avoid possible collisions compared with existing collision avoidance methods.


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