With the advantage of fast calculation and map resources on cloud control system(CCS), cloud-based predictive cruise control(CPCC) for heavy trucks has great potential to improve energy efficiency, which is significan...With the advantage of fast calculation and map resources on cloud control system(CCS), cloud-based predictive cruise control(CPCC) for heavy trucks has great potential to improve energy efficiency, which is significant to achieve the goal of national carbon neutrality. However, most investigations focus on the on-board predictive cruise control(PCC) system,lack of research on CPCC architecture under CCS. Besides, the current PCC algorithms have the problems of a single control target and high computational complexity, which hinders the improvement of the control effect. In this paper, a layered architecture based on CCS is proposed to effectively address the realtime computing of CPCC system and the deployment of its algorithm on vehicle-cloud. In addition, based on the dynamic programming principle and the proposed road point segmentation method(RPSM), a PCC algorithm is designed to optimize the speed and gear of heavy trucks with slope information. Simulation results show that the CPCC system can adaptively control vehicle driving through the slope prediction, with fuel-saving rate of 6.17% in comparison with the constant cruise control. Also,compared with other similar algorithms, the PCC algorithm can make the engine operate more in the efficient zone by cooperatively optimizing the gear and speed. Moreover, the RPSM algorithm can reconfigure the road in advance, with a 91% roadpoint reduction rate, significantly reducing algorithm complexity.Therefore, this study has essential research significance for the economic driving of heavy trucks and the promotion of the CPCC system.展开更多
As one of the most important components of the wideband wireless access technique, orthogonal frequency division multiplexing （OFDM） has a high usage rate of spectrum and combats inter-symbol interference （ISI） in...As one of the most important components of the wideband wireless access technique, orthogonal frequency division multiplexing （OFDM） has a high usage rate of spectrum and combats inter-symbol interference （ISI） in multi-path fading channel. However, when there are frequency offsets during the signal transmission, the inter-carrier interference （ICI） is introduced, which significantly degrades the performance. The existing ICI self-cancellation schemes such as PCC-OFDM are not optimum to minimize the interference considering both noise and ICI. In this paper, a new metric named S1NR （signal-to-interference- and-noise ratio） is proposed. We discuss the optimization issue when a constant frequency offset exists and in time-varying channels. The optimum weighting-coefficient-pair （OWCP） is obtained, which maximizes SINR theoretically through the alternant iteration algorithm. Simulations show that the performance of OWCP-OFDM is better than that of PCC-OFDM, especially when the frequency offset is large. Although the ICI self-cancellation scheme suffers bandwidth inefficiency, from the simulation results we can also see that the performance of OWCP-OFDM is much better than that of the standard OFDM systems with the same bandwidth efficiency when a frequency offset exists. Moreover, since the redundant modulation provides the capability to suppress ICI as well as a receiving SNR gain, it can be considered as exchanging the bandwidth for SNR.展开更多
基金supported by the National Key Research and Development Program (2021YFB2501003)the Key Research and Development Program of Guangdong Province (2019B090912001)the China Postdoctoral Science Foundation (2020M680531)。
文摘With the advantage of fast calculation and map resources on cloud control system(CCS), cloud-based predictive cruise control(CPCC) for heavy trucks has great potential to improve energy efficiency, which is significant to achieve the goal of national carbon neutrality. However, most investigations focus on the on-board predictive cruise control(PCC) system,lack of research on CPCC architecture under CCS. Besides, the current PCC algorithms have the problems of a single control target and high computational complexity, which hinders the improvement of the control effect. In this paper, a layered architecture based on CCS is proposed to effectively address the realtime computing of CPCC system and the deployment of its algorithm on vehicle-cloud. In addition, based on the dynamic programming principle and the proposed road point segmentation method(RPSM), a PCC algorithm is designed to optimize the speed and gear of heavy trucks with slope information. Simulation results show that the CPCC system can adaptively control vehicle driving through the slope prediction, with fuel-saving rate of 6.17% in comparison with the constant cruise control. Also,compared with other similar algorithms, the PCC algorithm can make the engine operate more in the efficient zone by cooperatively optimizing the gear and speed. Moreover, the RPSM algorithm can reconfigure the road in advance, with a 91% roadpoint reduction rate, significantly reducing algorithm complexity.Therefore, this study has essential research significance for the economic driving of heavy trucks and the promotion of the CPCC system.
基金Project (No. 2006AA01Z273) supported by the Hi-Tech ResearchDevelopment Program (863) of China
文摘As one of the most important components of the wideband wireless access technique, orthogonal frequency division multiplexing （OFDM） has a high usage rate of spectrum and combats inter-symbol interference （ISI） in multi-path fading channel. However, when there are frequency offsets during the signal transmission, the inter-carrier interference （ICI） is introduced, which significantly degrades the performance. The existing ICI self-cancellation schemes such as PCC-OFDM are not optimum to minimize the interference considering both noise and ICI. In this paper, a new metric named S1NR （signal-to-interference- and-noise ratio） is proposed. We discuss the optimization issue when a constant frequency offset exists and in time-varying channels. The optimum weighting-coefficient-pair （OWCP） is obtained, which maximizes SINR theoretically through the alternant iteration algorithm. Simulations show that the performance of OWCP-OFDM is better than that of PCC-OFDM, especially when the frequency offset is large. Although the ICI self-cancellation scheme suffers bandwidth inefficiency, from the simulation results we can also see that the performance of OWCP-OFDM is much better than that of the standard OFDM systems with the same bandwidth efficiency when a frequency offset exists. Moreover, since the redundant modulation provides the capability to suppress ICI as well as a receiving SNR gain, it can be considered as exchanging the bandwidth for SNR.
