Study on the braking force allocation dynamic control strategy based on the fuzzy control logic

Liang, Chao; Yao, Liang; Yin, Jiankun; Chao, LiBo; Wei, Wei

doi:10.1109/icieem.2011.6035237

Cited by 6 publications

(2 citation statements)

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“…It also uses battery temperature to produce a compensation coefficient in order to limit the regenerated current. A control strategy using a couple of fuzzy logic controllers is studied in (Chu et al, 2011b) for adjusting the braking force allocation. As input information, it is used the brake pedal displacement, and the slip ratio of the wheel, not being useful in traffic simulators.…”

Section: Related Workmentioning

confidence: 99%

Electrical vehicle modeling: A fuzzy logic model for regenerative braking

Maia

Silva

Araújo

et al. 2015

Expert Systems with Applications

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Highlights• A fuzzy logic model for modeling regenerative braking systems is presented.• Model output is the ratio of regenerative braking force to the total braking force.• Model can be adapted to be used in traffic simulators like the SUMO simulator.• Real data was gathered from short and long-distance field tests with a Nissan LEAF.• Results were compared with real-world data obtained with a Nissan LEAF in road tests. AbstractR2Q3 This paper presents a fuzzy logic model of regenerative braking (FLmRB) for modeling EVs' regenerative braking systems (RBS). The model has the vehicle's acceleration and jerk, and the road inclination as input variables, and the output of the FLmRB is the regeneration factor, i.e. the ratio of regenerative braking force to total braking force. The regeneration factor expresses the percentage of energy recovered to the battery from braking. The purpose of the FLmRB development is to create realistic EV models using as least as possible manufacturers intellectual property data, and avoiding the use of EV on-board sensors. To tune the model, real data was gathered from short and long-distance field tests with a Nissan LEAF and compared with two types of simulations, one using the proposed FLmRB, and the other considering that all the braking force/energy is converted to electric current and returned back to charge the battery (100% regeneration). The results show that the FLmRB can successfully infer the regenerative braking factor from the measured EV acceleration and jerk, and road inclination, without any knowledge about the EV brake control strategy.

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Section: Related Workmentioning

confidence: 99%

Electrical vehicle modeling: A fuzzy logic model for regenerative braking

Maia

Silva

Araújo

et al. 2015

Expert Systems with Applications

View full text Add to dashboard Cite

show abstract

“…Where, β FR is defined as the allocation ratio of the front axle braking force to the total braking force, β EH is defined the allocation ratio of regenerative braking force on the driving axle to the total braking [4], T motor_max is the maximum regenerative braking force, T req is the braking demand force At the second state, the rear axle must have braking force which is based on the ECE regulation. β FR and β EH can be figured out as follow.…”

Section: Braking Force Distribution Strategymentioning

confidence: 99%