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The article presents an analysis of the optimal control of speed and regenerative braking in an electric vehicle (EV). The presence of the continuous generating power is one of the major challenges for battery charging of electric vehicle. In order to meet the demand of continuous power, electric vehicles are driven by solar PV arrays. Initially, maximum power extraction (MPPT) is assessed from a solar photovoltaic (PV) array using the P&O method. The outputs of the solar PV array are integrated with electric vehicles. Such integration creates the problem of maintaining the power quality. The existing methods also address the issue of optimal speed and torque control with high transients and more settling time. In this article, an electric vehicle is modeled first and then operated in regenerative braking mode. To address the shortcomings of existing methods, the linear quadratic regulator (LQR) method is used; then, fuzzy logic controller (FLC)-based LQR is used for optimal speed and torque control during electric vehicle regenerative braking. In terms of reduced settling time and improved peak overshoot, optimal speed and regenerative torque of electric vehicles are better realized with LQR-based FLCs than with LQR controllers. In addition to this, stopping speed characteristics with various electrical parameters (voltage, current, and flux) have been analyzed with different methods in which LQR-based FLC shows its dominance to attain zero speed in regenerative mode with more sharp characteristics.

Purpose: Zinc (Zn) deficiency in soils and crop plants is a global concern, undesirably influencing crop productivity, crop quality and human health. Farmers add Zn to soil through different agro-inputs by various means, which influences its behaviour in soil-plant systems. Efficient soil Zn management by estimating soil Zn fractions and assessing their contribution towards phyto-availability of Zn, crop yield and crop Zn uptake is therefore crucial for achieving sustainable crop yield. Methods: We carried out the present study to assess the impact of different nutrient management practices (NMP) for 20 years on yield, Zn uptake by maize (Zea maysL.), and Zn distribution in Vertisol. The NMP practices consisted of different levels of nitrogen (N) - phosphorus (P) - potassium (K) supplied through inorganic fertilizers and various organic materials such as farmyard manure (FYM), poultry manure, urban compost, maize residue, Gliricidia sepiumloppings alone or in combination. Results: Application of 5 Mg FYM ha−1along with 75% of soil-test-crop response (STCR) based NPK resulted in highest grain and stover yield. Zinc content and uptake by maize grain varied significantly, and ranged from 19.6 to 29.3 mg kg−1and from 34.2 to 167 g ha−1, respectively under different treatments. Annual addition of 20 Mg FYM ha−1recorded the highest soil organic carbon content of 8.94 g kg−1. Addition of 1 Mg poultry manure ha−1with 75% STCR based NPK, 5 Mg urban compost ha−1with 75% STCR based NPK, and 2 Mg Gliricidia sepiumloppings ha−1along with 5 Mg maize residue mulch ha−1and 5 Mg FYM ha−1to soil recorded relatively higher levels DTPA-Zn of 2.48, 2.32 and 2.18 mg kg−1, respectively. Different treatments significantly influenced sorbed (Sorb-Zn), easily reducible Mn bound (ERMn-Zn), carbonate bound (Carb-Zn), organic matter bound (OM-Zn), Fe and Al oxide bound (FeOX-Zn) and residual (Res-Zn) Zn in soil. Zinc fractions in soil across the different treatments followed the order: Res-Zn (~ 71– 81%) > ERMn-Zn (~ 9.48–11.9%) > Sorb-Zn (~ 3.16–5.32%) > FeOX-Zn (~ 2.61–7.38%), Carb-Zn (~ 2.35–3.67%), OM-Zn (~ 0.19–0.64%), and water-soluble Zn (WS-Zn) (≤ 0.19%). DTPA-Zn was positively and significantly correlated with WS-Zn, Sorb-Zn, ERMn-Zn, Carb-Zn, OM-Zn and FeOX-Zn. Path coefficient analysis revealed direct effect of Sorb-Zn, ERMn-Zn and Carb-Zn on Zn uptake by maize crop. Conclusion: Integrated use of organic and inorganic sources of nutrients (5 Mg FYM ha−1+ 75% of STCR based NPK) found to be superior for achieving higher maize yield and soil Zn availability. Various Zn fractions contributed Zn fractions towards Zn availability in soil, yield, Zn content and uptake by maize. This information is useful for managing Zn in soil-plant systems for higher yield and Zn uptake by maize under different nutrient management scenarios.