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Energy-management system for a hybrid electric vehicle, using ultracapacitors and neural networks
Open accessAbstract
A very efficient energy-management system for hybrid electric vehicles (HEVs), using neural networks (NNs), was developed and tested. The system minimizes the energy requirement of the vehicle and can work with different primary power sources like fuel cells, microturbines, zinc-air batteries, or other power supplies with a poor ability to recover energy from a regenerative braking, or with a scarce power capacity for a fast acceleration. The experimental HEV uses lead-acid batteries, an ultracapacitor (UCAP) bank, and a brushless dc motor with nominal power of 32 kW, and a peak power of 53 kW. The digital signal processor (DSP) control system measures and stores the following parameters: primary-source voltage, car speed, instantaneous currents in both terminals (primary source and UCAP), and actual voltage of the UCAP. When UCAPs were installed on the vehicle, the increase in range was around 5.3% in city tests. However, when optimal control with NN was used, this figure increased to 8.9%. The car used for this experiment is a Chevrolet light utility vehicle (LUV) truck, similar in shape and size to Chevrolet S-10, which was converted to an electric vehicle (EV) at the Universidad Catolica de Chile. Numerous experimental tests under different conditions are compared and discussed.
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Citations
Cited by
Emadi, A., Lee, Y. J., & Rajashekara, K. (2008) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2008.922768 · Cited by 1,461
Review on Control of DC Microgrids
Meng, L., Shafiee, Q., Ferrari Trecate, G., Karimi, H., Fulwani, D., Lu, X., & Guerrero, J. M. (2017) · IEEE Journal of Emerging and Selected Topics in Power Electronics · doi:10.1109/jestpe.2017.2690219 · Cited by 513
Control Strategy of Fuel Cell and Supercapacitors Association for a Distributed Generation System
Thounthong, P., Rael, S., & Davat, B. (2007) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2007.896477 · Cited by 355
A Hybrid Fuel Cell Power System
Jin, K., Ruan, X., Yang, M., & Xu, M. (2009) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2008.2008336 · Cited by 331
Energy Management Power Converters in Hybrid Electric and Fuel Cell Vehicles
Lai, J.-S., & Nelson, D. J. (2007) · Proceedings of the IEEE · doi:10.1109/jproc.2006.890122 · Cited by 318
Metadata
- Authors
- Moreno, J., Ortuzar, M. E., & Dixon, J. W.
- Venue
- IEEE Transactions on Industrial Electronics
- Published
- 2006-04
- Volume
- 53
- Issue
- 2
- Pages
- 614-623
- ISSN
- 0278-0046 (ISSN-L)
- 1557-9948
- OpenAlex
- W2153909224
- Cited by
- 748
- References
- 0
- FWCI
- 95.48
- Type
- journal article
- Language
- en
- Open access
- green
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- Moreno, J., Ortuzar, M. E., & Dixon, J. W. (2006). Energy-management system for a hybrid electric vehicle, using ultracapacitors and neural networks. IEEE Transactions on Industrial Electronics. https://doi.org/10.1109/tie.2006.870880
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