Effect of socio-economic factors on EV/HEV/PHEV adoption rate in Ontario

Ahmadi, Lena; Croiset, Eric; Elkamel, Ali; Douglas, Peter; Entchev, Evgueniy; Abdul‐Wahab, Sabah A.; Yazdanpanah, Pedram

doi:10.1016/j.techfore.2015.06.012

Cited by 21 publications

(7 citation statements)

References 22 publications

(33 reference statements)

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“…Awareness about benefits of electric vehicles increases adoption in the community [59]. Hence, people will switch to shared-mobility if they are aware of its benefits, and are being recognized in the society for adopting shared-mobility.…”

Section: Policy Recommendationsmentioning

confidence: 99%

A Review of Electric Vehicle Lifecycle Emissions and Policy Recommendations to Increase EV Penetration in India

2018

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Electric vehicles reduce pollution only if a high percentage of the electricity mix comes from renewable sources and if the battery manufacturing takes place at a site far from the vehicle use region. Industries developed due to increased electric vehicle adoption may also cause additional air pollution. The Indian government has committed to solving New Delhi's air pollution issues through an ambitious policy of switching 100% of the light duty consumer vehicles to electric vehicles by 2030. This policy is based on vehicle grid interaction and relies on shared mobility through the electric vehicle fleet. There are several human behavioral changes necessary to achieve 100% adoption of electric vehicles. This paper reviews different steps in the lifecycle of an electric vehicle (EV), their impact on environmental emissions, and recommends policies suitable for different socio-economic group that are relevant to the Indian market. To reduce air pollution through adoption of electric vehicles, the Indian government needs to adopt policies that increase sale of electric vehicles, increase percentage of renewable energy in the electricity mix, and prevent air pollution caused from battery manufacturing. The recommended policies can be customized for any market globally for reducing air pollution through increased adoption of electric vehicles.

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Section: Policy Recommendationsmentioning

confidence: 99%

A Review of Electric Vehicle Lifecycle Emissions and Policy Recommendations to Increase EV Penetration in India

2018

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“…Attention to the advantages of EVs expands the reception of the network. 34 In this manner, if individuals know and perceived of their advantages they are going to change to shared mobility in the public arena.…”

Section: Attracting Customers Basing On Policy Aspectsmentioning

confidence: 99%

“…Promoting effort to make shared mobility socially satisfactory in the four‐wheeler network of proprietors: Government supports existing four‐wheeler proprietors to change to shared mobility by urging them to profit by advantages, for example, acknowledgment of nearby media. Attention to the advantages of EVs expands the reception of the network 34 . In this manner, if individuals know and perceived of their advantages they are going to change to shared mobility in the public arena. Keep on subsidized projects for the generation of sustainable energy: EVs create less discharge just if the fuel blend depends on inexhaustible energy 35 discourse in the segments above.…”

Section: Attracting Customers Basing On Policy Aspectsmentioning

confidence: 99%

Electric vehicles charging in India: Infrastructure planning and policy aspects

et al. 2022

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Following years, electric vehicles (EVs) are promising technology for shifting scattered exhaust emissions in mega‐cities to integrated power plants in rural areas, especially in urban areas. Transport sector electrification and increased popularity of EVs make scientists and researchers, search for charging stations. The ideal position, charge scheduling, and developed charging infrastructure are the primary concern for the large‐scale deployment of EVs. This paper describes the possible demand for EVs charging station infrastructure and challenges in the Indian situation. Along these lines, this study also provides the research community with the latest developments and research findings of charging infrastructure for EVs in India.

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“…3 By analyzing the driver's demand and splitting power among different energy systems, the EMS enables the power components to operate in a high-efficiency area. 4 Obtaining the optimal power split and the lowest cost is the key to the EMS. At present, there are a lot of studies on EMS of HEVs.…”

Section: Introductionmentioning

confidence: 99%

“…3 By analyzing the driver’s demand and splitting power among different energy systems, the EMS enables the power components to operate in a high-efficiency area. 4…”

Section: Introductionmentioning

confidence: 99%

A driving-cycle predictive control approach for energy consumption optimization of hybrid electric vehicle

Liu

Shi

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part D:

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This paper proposes an adaptive control strategy of fuel consumption optimization for hybrid electric vehicles (HEVs). The strategy combines a moving-horizon-based nonlinear autoregressive (NAR) algorithm, a backpropagation (BP) neural network algorithm, and an equivalent consumption minimization strategy (ECMS) method to reduce energy consumption. The moving-horizon-based NAR algorithm is applied to predict the short future driving cycle. The BP neural network algorithm is employed to recognize the driving cycle types, which provides the basis for the adaptive ECMS. Based on the abovementioned approach, the power split of the fuel and electric system is determined in advance, and the optimal control of energy efficiency is achieved. A driving experiment platform is established, taking a synthetic driving cycle composed of several standard driving cycles as the target cycle, and the control strategy is tested by the driver’s real operation. The results indicate that, compared with the basic ECMS, the A-ECMS with moving-horizon-based driving cycle prediction and recognition has better SOC (state of charge) retention and reduces the fuel consumption of the engine by 3.31%, the equivalent fuel consumption of the electric system by 0.9 L/100 km and the total energy consumption by 1 L/100 km. Adaptive ECMS based on driving cycle prediction and recognition is an effective method for the energy management of HEVs.

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Effect of socio-economic factors on EV/HEV/PHEV adoption rate in Ontario

Cited by 21 publications

References 22 publications

A Review of Electric Vehicle Lifecycle Emissions and Policy Recommendations to Increase EV Penetration in India

A Review of Electric Vehicle Lifecycle Emissions and Policy Recommendations to Increase EV Penetration in India

Electric vehicles charging in India: Infrastructure planning and policy aspects

A driving-cycle predictive control approach for energy consumption optimization of hybrid electric vehicle

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