scholarly journals Improving Electric Vehicle Energy Efficiency with Two-Speed Gearbox

Author(s):  
Heikki Laitinen ◽  
Antti Lajunen ◽  
Kari Tammi
Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3147
Author(s):  
Kiyoung Kim ◽  
Namdoo Kim ◽  
Jongryeol Jeong ◽  
Sunghwan Min ◽  
Horim Yang ◽  
...  

Many leading companies in the automotive industry have been putting tremendous effort into developing new powertrains and technologies to make their products more energy efficient. Evaluating the fuel economy benefit of a new technology in specific powertrain systems is straightforward; and, in an early concept phase, obtaining a projection of energy efficiency benefits from new technologies is extremely useful. However, when carmakers consider new technology or powertrain configurations, they must deal with a trade-off problem involving factors such as energy efficiency and performance, because of the complexities of sizing a vehicle’s powertrain components, which directly affect its energy efficiency and dynamic performance. As powertrains of modern vehicles become more complicated, even more effort is required to design the size of each component. This study presents a component-sizing process based on the forward-looking vehicle simulator “Autonomie” and the optimization algorithm “POUNDERS”; the supervisory control strategy based on Pontryagin’s Minimum Principle (PMP) assures sufficient computational system efficiency. We tested the process by applying it to a single power-split hybrid electric vehicle to determine optimal values of gear ratios and each component size, where we defined the optimization problem as minimizing energy consumption when the vehicle’s dynamic performance is given as a performance constraint. The suggested sizing process will be helpful in determining optimal component sizes for vehicle powertrain to maximize fuel efficiency while dynamic performance is satisfied. Indeed, this process does not require the engineer’s intuition or rules based on heuristics required in the rule-based process.


2021 ◽  
Author(s):  
Ramkumar Iyer ◽  
Zhichao Chen ◽  
PS SATYANARAYANA ◽  
ANTARA BHATTACHARJEE ◽  
NAVNEET JHA ◽  
...  

2020 ◽  
Vol 143 (3) ◽  
Author(s):  
Yuanzhi Liu ◽  
Jie Zhang

Abstract Energy management plays a critical role in electric vehicle (EV) operations. To improve EV energy efficiency, this paper proposes an effective model predictive control (MPC)-based energy management strategy to simultaneously control the battery thermal management system (BTMS) and the cabin air conditioning (AC) system. We aim to improve the overall energy efficiency and battery cycle-life, while retaining soft constraints from both BTMS and AC systems. The MPC-based strategy is implemented by optimizing the battery operations and discharging schedules to avoid a peak load and by directly utilizing the regenerative power instead of recharging the battery. Compared with the benchmark system without any control coordination between BTMS and AC, the proposed MPC-based energy management has shown a 4.3% reduction in the recharging energy and a 6.5% improvement for the overall energy consumption. Overall, the MPC-based energy management is a promising solution to enhance the battery efficiency for EVs.


2015 ◽  
Vol 51 (4) ◽  
pp. 2874-2883 ◽  
Author(s):  
Katsuhiko Urase ◽  
Noboru Yabu ◽  
Kyohei Kiyota ◽  
Hiroya Sugimoto ◽  
Akira Chiba ◽  
...  

2010 ◽  
Vol 4 (1) ◽  
pp. 9-13 ◽  
Author(s):  
Rengui Lu ◽  
Aochi Yang ◽  
Yufeng Xue ◽  
Lichao Xu ◽  
Chunbo Zhu

2012 ◽  
Vol 165 ◽  
pp. 48-52
Author(s):  
M. Sabri ◽  
M. Rezal

This paper presents a study of the power needed by batteries to drive an electric vehicle for specific purpose using basic theory and fundamental formulas. In order to develop an electric vehicle, the energy and power requirements of the vehicle in various driving environments need to be estimated. The energy efficiency of a vehicle depends primarily upon the specific vehicle design and the environment in which the vehicle is operated. Basic parameters are set off in the beginning such as car weight and much more comprehensive parameter will developed later such as vehicle cruising velocity. Generally, four forces affect vehicle motion; aerodynamic resistance, rolling resistance, climbing resistance and acceleration power. The total of these four forces will result in an estimation of maximum power needed for the electric vehicle.


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