Discuss about the Review on Electric Regenerative Braking System.
They analysed hybrid electric vehicle (HEV) with regenerative breaking system to develop a continuously variable transmission (CVT) theoretical loss model. As CVT efficiency varies with the dissimilar operating conditions, they calculated the transmission efficiency during the regenerative breaking by developing a CVT theoretical torque model which leads to battery–front motor–CVT joint operating efficiency. They concluded that CVT torque loss depends on the input torque, speed ratio and input speed. They proposed a strategy to entirely utilize the motor breaking power based on the motor maximum breaking force and required breaking force. They performed the simulation for three breaking conditions and established that strategy adopted by them enriches the motor operating efficiency and front breaking power (Yang Yang, Xiaolong He, Yi Zhang, 2018).
They conducted their study on utilizing the energy generated by electric vehicles for different braking load. There developed a model of electric regenerative braking system to analyse its performance. The model developed by them is operated at 12V and a bear a variable load for storing 0.84W of energy. They found that that application of 648gm and 72gm braking loads can recharges the battery by 0.80C and 0.15C and concluded that increment in the braking load increase the recharging capacity of the developed system. They found that braking load is inversely proportional to the rpm, the shaft rpm are 1435 and 2019 at maximum and minimum load respectively (Mandal, Sarker, Rahman, & Beg, 2017).
They studied the regenerative braking strategy of electric vehicle. They optimized the different parameters by utilizing (PSO) particle swarm optimization technique. They governing parameters of their study are breaking strength, state of charge, battery charge capacity and speed. They concluded that PSO model can enhance the stability of the vehicle and recovery of braking energy (Zhijun, Dongdong, & Jingbo, 2017).
He studied the energy flow into the battery and out from the battery MY2012 and MY2013. He compared their regenerative braking efficiency. From his analyses he concluded that (KERS) kinetic energy resource system is best suit to increase the efficiency of passenger cars. He analysed the braking power, propulsive and energies utilizing the velocity. From his results he concluded that there is very small improvement in case of M2013 for regenerative braking efficiency and is equal to +6.57% (Boretti, 2016).
They design and developed a new technique to improve the energy efficiency of electric vehicle using regenerative braking system energy flow. They proposed two methodologies for control system “parallel control strategy” and ‘‘serial 1 control strategy”. They tested their methodologies under the CTCRDC (China typical city regenerative driving cycle) with three different strategy and evaluate two parameters energy transfer efficiency and regenerative driving range and found that these two parameters varies up to 41.09% and 24.63% respectively (Qiu & Wang, 2016).
They developed a model to improve the efficiency and braking performance of the electric vehicle based on a hydraulic unit. They also validated their results by developing a same mathematical model on the MATLAB/Simulink. They present a break-by-wire (BBW) system based on the direct-drive electro-hydraulic brake (DDEHB) unit system. They concluded that DDHEB can improve the braking safety by handling it continuously and rapidly. They concluded that their model supply the regenerative force if it is inadequate which decreases the pollution and fuel consumption. They concluded that 91% of the braking efficiency is recovered in case of light braking and 56% in general (Xiaoxiang Gong, Siqin Chang, 2016).
He designed a regenerative braking system to improve the efficiency of electrical vehicle. He incorporated the different parameters like, vehicle speed, capacity of battery recharging, motor braking power. He simulated his result on the software MATLAB/Simulink environment. From the results He concluded that the efficiency can be recovered by maximum of 60% (Gou, 2016).
He gives a regenerative breaking system for electric automobiles based on PWM control equivalent model. First integrated controlling system is introduced by him then composition principle is applied for regenerative braking system. He used hydraulic ABS model with double-pipeline, four-channel, and four-sensor. He also conducted the experiments for the same scenario to find the efficiency of the system and validate their simulation results (Zhuan, 2016).
They reviewed the study on the regenerative braking system effect on the conventional electrical vehicles. They proposed two evaluation parameters (contribution ratio to energy efficiency improvement and contribution ratio to driving range extension) and methodologies. They analysed the electric vehicle energy flow and proposed the techniques to quantity the impact of regenerative braking on the electric vehicle performance. They found the contribution ratio to energy efficiency improvement and contribution ratio to driving range extension to be 11.18% and 12.58% respectively (Lv, Zhang, Li, & Yuan, 2015).
They designed cost-effective hybrid electrical energy storage (HEES) system for electrical vehicle (EV). For their work they used lithium-ion battery bank and super-capacitor bank. They targeted their study towards reducing the overall cost (sum of capital and operational cost) of the system utilizing battery cycle efficiency, super-capacitor bank characteristics and EV dynamics. They applied their model on a well-known vehicle dynamics model. At the end presented an algorithm which shows that model developed by them (Lithium-ion battery) outdoes the conventional EC HEES system by 20.91% for overall cost and 30.29% for fuel economy (Zhu et al., 2014).
They presented a regenerative braking system (RBS) based on the fly-wheel for energy recovery. Their model store the kinetic energy generated by intermittent energy resources with the help of a flywheel with a progressive braking system and epicyclic gear train. Their model is adaptable in renewable energy recourses like wind and solar (Hsu & Fellow, 2013).
They define all the regenerative braking strategies for a three rear-wheel hybrid vehicle. They targeted their study towards finding all the losses during energy capture and then utilizing these results to design an optimal ergative strategy. They minimised the transfer loss during the kinetic energy recapture to develop the regenerative braking strategy from the efficiency map. They developed two models one without consideration of slip and other with consideration of slip. They concluded that the slip condition can also affect the final solution of the problem. They concluded that optimal criteria give the best results in respect of regenerative braking system. Experiments conducted by them shows that one can capture the 90% of the optimal recaptured energy if deceleration is chosen between 2 to 3 m/s2 (Mammosser, Boisvert, & Micheau, 2013).
They modelled heavy vehicle hydraulic regenerative braking system for urban driving conditions. They utilized MATLAB/Simulink to model the three-axle hydraulic regenerative braking. They concluded that their model can reduce the fuel consumption by 21.7% and 11.2-17% for legislative driving. They also run some simulation on the hills and concluded that model can reduce the fuel consumption for hills by 29.4% at 30 mile/h speed (Midgley, Cathcart, & Cebon, 2013).
They conducted their study to optimize the regenerative braking and slip control a wheel for in-wheel motor equipped vehicle. They work on reducing the CO2 emission by utilizing an in-wheel motor to control the torque at the rear wheels. They also targeted their study towards to control wheel slip on any road condition by suggesting a method based on the control of varying friction torque (Solliec, Chasse, & Geamanu, 2013).
He conducted the simulation on the hydraulic regenerative braking system for off-road vehicles and heavy duty trucks. He targeted his study towards enriching the regenerative braking energy and engine efficiency of parallel hydraulic regenerative braking vehicle (PHRBV). The parameters studied by him are torque distribution, vehicle load, fuel economy. He developed a real time control energy distribution for the projected PHRBV by utilizing a fuzzy torque control strategy. He modelled his engine to run at a speed of 2200 rpm when pumping fluid. He concluded that the developed PHRBV enriches the braking regenerative potential andworking conditions,this minimises energy density of accumulator and improve the fuel economy of the system (Kumar, 2012).
They conducted their study on optimizing the parameters of hybrid propulsion system (marine vessels). They developed a multi-objective genetic algorithm to optimize the propulsion components like fuel consumption and weight of installation. They utilized MATLAB/Simulink for modelling of the system. They utilized lithium-ion batteries and permanent magnet machine and concluded that lithium battery gives better specific energy capacity which in turn increases the performance of marine vessel (Sciberras & Grech, 2012).
They conducted their study to optimize the performance of electric bus by using regenerative braking control. The bus is linked to an anti-lost braking system (ABS). They designed a real-time brake controller to regulate the tactics. They conducted the simulation on the optimization tool of MATLAB/Simulink. They targeted their study towards giving a better solution in the situation when frictional braking comes under ABS control. They concluded that ABS with regenerative braking system attains good result compared to pneumatic ABS and regenerative braking control (Zhang, Kong, Chen, & Chen, 2011).
He works on improving the hybrid electrical vehicle performance by utilizing the vehicle regenerative braking energy. He examined the driving cycle phase and recuperation energy relationship for batteries of hybrid electric vehicles. He utilized MATLAB/Simulink software for modelling of the work. He concluded that regenerative braking improve the performance and decreases the fuel consumption of the conventional hybrid electric vehicle. He concluded that braking energy can increase up to 20% and 50% respectively for city urban field and large cities respectively (Mohamed, 2011).
References
Yang Yang, Xiaolong He, Yi Zhang, D. Q. (2018). Regenerative Braking Compensatory Control Strategy Considering CVT Power Loss for Hybrid Electric Vehicles. Energies, 11, 497, 1–15. https://doi.org/10.3390/en11030497
Mandal, S., Sarker, M. R. I., Rahman, M. S., & Beg, M. R. A. (2017). An Analysis of Braking Energy Regeneration in Electric Vehicles. International Journal of Renewable Energy Research, 7(3), 999–1006.
Zhijun, G., Dongdong, Y., & Jingbo, W. (2017). Optimization of Regenerative Braking Control Strategy for Pure Electric Vehicle. Applied Mechanics and Materials, 872, 331–336. https://doi.org/10.4028/www.scientific.net/AMM.872.331
Boretti, A. (2016). Comparison of Regenerative Braking Efficiencies of MY2012 and MY2013 Nissan Leaf. International Journal of Engineering and Technology Innovation, 6(3), 214–224.
Qiu, C., & Wang, G. (2016). New evaluation methodology of regenerative braking contribution to energy efficiency improvement of electric vehicles. Energy Conversion And Management, 119, 389–398. https://doi.org/10.1016/j.enconman.2016.04.044
Xiaoxiang Gong, Siqin Chang, L. J. and X. L. (2016). Research on regenerative brake technology of electric vehicle based on direct-drive electric-hydraulic brake system. International Journal of Vehicle Design, 70(1), 1–28.
Gou, Y. (2016). Research on Electric Vehicle Regenerative Braking System and Energy Recovery. International Journal of Hybrid Information Technology, 9(1), 81–90.
Zhuan, Y. (2016). Regenerative Braking Scheme of Pure Electric Vehicle Electro Hydraulic Compound Braking. Journal of Residuals Science & Technology, 13(7), 1–5. https://doi.org/10.12783/issn.1544-8053/13/7/90
Lv, C., Zhang, J., Li, Y., & Yuan, Y. (2015). Mechanism analysis and evaluation methodology of regenerative braking contribution to energy efficiency improvement of electrified vehicles. Energy Conversion And Management, 92, 469–482. https://doi.org/10.1016/j.enconman.2014.12.092
Zhu, D., Yue, S., Park, S., Wang, Y., Chang, N., & Pedram, M. (2014). Cost-Effective Design of a Hybrid Electrical Energy Storage System for Electric Vehicles. Wiki Article.
Hsu, T., & Fellow, A. (2013). On a Flywheel-Based Regenerative Braking System for Regenerative Energy Recovery. Proceedings of Green Energy and Systems Conference.
Mammosser, D., Boisvert, M., & Micheau, P. (2013). Designing regenerative braking strategies for electric vehicles with an efficiency map Abstract?: Mots clefs?: Optimization criteria. Congres Francais de Mecanique, 1–6.
Midgley, W. J. B., Cathcart, H., & Cebon, D. (2013). Modelling of hydraulic regenerative braking systems for heavy vehicles. 2 Proc IMechE Part D: J Automobile Engineering, 0(0), 1–13. https://doi.org/10.1177/0954407012469168
Solliec, G. Le, Chasse, A., & Geamanu, M. (2013). Regenerative braking optimization and wheel slip control for a vehicle with in-wheel motors. IFAC Symposium on Advances in Automotive Control (Vol. 46). IFAC. https://doi.org/10.3182/20130904-4-JP-2042.00043
Kumar, E. R. A. (2012). Hydraulic Regenerative Braking System. International Journal of Scientific & Engineering Research, 3(4), 1–12.
Sciberras, E., & Grech, A. (2012). Optimization of Hybrid Propulsion Systems. International Journal on Marine Navigation and Safety of Sea Transportation, 6(4), 539–546.
Zhang, J., Kong, D., Chen, L., & Chen, X. (2011). Optimization of control strategy for regenerative braking of an electrified bus equipped with an anti-lock braking system. Proc. IMechE Vol. 000 Part D: J. Automobile Engineering Downloaded, 0, 1–13. https://doi.org/10.1177/0954407011422463
Mohamed, M. (2011). Improving the performance of a hybrid electric vehicle by utilization regenerative braking energy of vehicle. International Journal of Energy and Environment, 2(1), 161–170.
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